Philippa Kaur

Calculation of flight-step headings and movementTerms defining flight-step movement, precision and geophysical orientation cues are listed in Table 1. Since seasonal migration nearly ubiquitously proceeds from higher to lower latitudes, it is convenient to define headings clockwise from geographic South (counter-clockwise from geographic North for migration commencing in the Southern Hemisphere). Assuming a spherical Earth, a sequence of N migratory flight-steps with corresponding headings, αi, i = 0,…, N−1, the latitudes, ∅i+1, and longitudes, λi+1, on completion of each flight-step can be calculated using the Haversine Equation76, which we approximated by stepwise planar movement using Eqs. (1) and (2). For improved computational accuracy and to accommodate within flight-step effects, we updated simulated headings and corresponding locations hourly. A migrant’s flight-step distance ({R}_{{{mathrm {step}}}}=3.6{V}_{{mathrm {a}}}{cdot n}_{{mathrm {H}}}/{R}_{{{mathrm {Earth}}}}) (in radians), depends on its flight speed, Va (m/s) relative to the mean Earth radius REarth (km), and flight-step hours, nH. With a geomagnetic in-flight compass, expected hourly geographic headings are modulated by changes in magnetic declination, i.e., the clockwise difference between geographic and geomagnetic South10,32.Formulation of compass coursesFor simplicity, we consider the case of a single inherited or imprinted heading. This can be extended to include sequences of preferred headings. Expected geographic loxodrome headings remain unchanged en route, i.e.,$${bar{{{{{{rm{alpha }}}}}}}}_{i}={bar{{{{{{rm{alpha }}}}}}}}_{0}$$
(5)
Relative to geographic axes, expected geomagnetic loxodrome headings remain unchanged relative to proximate geomagnetic South, i.e., are offset by geomagnetic declination on departure (updated hourly in simulations)$${bar{{{{{{rm{alpha }}}}}}}}_{i}={bar{{{{{{rm{alpha }}}}}}}}_{0}+{delta }_{{mathrm {m}},i}$$
(6)
As described and illustrated in detail by Kiepenheuer13, the magnetoclinic compass was hypothesized to explain the prevalence of “curved” migratory bird routes, i.e., for which local geographic headings shift gradually but substantially en route. A migrant with a magnetoclinic compass adjusts its heading at each flight-step to maintain a constant transverse component, γ′, of the experienced inclination angle, γ, so that error-free headings are (see Fig. S5 in ref. 34)$${{bar{{{{{{rm{alpha }}}}}}}}_{i}={{sin }}}^{-1}left(frac{{{tan }}{gamma }_{i}}{{{tan }}{gamma }^{{prime} }}right){={{sin }}}^{-1}left(frac{{{tan }}{gamma }_{i}{{sin }}{bar{{{{{{rm{alpha }}}}}}}}_{0}}{{{tan }}{gamma }_{0}}right).$$
(7)
In a geomagnetic dipole field, the horizontal (Bh) and vertical (Bz) field, and therefore also inclination, each depends solely on geomagnetic latitude, ∅m:(gamma ={{{tan }}}^{-1}left({B}_{{mathrm {z}}}/{B}_{{mathrm {h}}}right)={{{tan }}}^{-1}left(2{{sin }}{phi }_{{mathrm {m}}}/{{cos }}{phi }_{{mathrm {m}}}right)={{{tan }}}^{-1}left(2{{tan }}{phi }_{{mathrm {m}}}right).) The projected transverse component, therefore, becomes$${gamma }^{{prime} }={{{tan }}}^{-1}left(frac{{{tan }}{gamma }_{0}}{{{sin }}{bar{{{alpha }}}}_{0}}right)={{{tan }}}^{-1}left(frac{2{{tan }}{{{phi }}}_{{mathrm {m}},0}}{{{sin }}{bar{{{{{{rm{alpha }}}}}}}}_{0}}right),$$which can be substituted into Eq. (7) to produce a closed formula for magnetoclinic headings in a dipole as a function of geomagnetic latitude$${bar{{{{{{rm{alpha }}}}}}}}_{i}left({{{phi }}}_{{mathrm {m}},i}right)={{{sin }}}^{-1}left(frac{{{sin }}{bar{{{{{{rm{alpha }}}}}}}}_{0}}{{{tan }}{{{phi }}}_{{mathrm {m}},0}}cdot {{tan }}{{{phi }}}_{{mathrm {m}},i}right),$$
(8)
with the expected initial heading, ({bar{{{{{{rm{alpha }}}}}}}}_{0}), and initial geomagnetic latitude, ∅m,0, being constants. Equations (7) and (8) have no solution when inclination increases en route, which could occur following substantial orientation error or in strongly non-dipolar fields. We followed previous studies in allowing magnetoclinic migrants to head towards magnetic East or West until inclination decreased sufficiently33,34,46, but also included orientation error based on the modelled compass precision.To assess sun-compass sensitivity algebraically, and also to improve computational efficiency, we used a closed-form equation for sunset azimuth, θs (derived in Supplementary Note 3 and see ref. 23),$${theta }_{{mathrm {s}}}={{{cos }}}^{-1}left(frac{-{{sin }}{delta }_{{mathrm {s}}}}{{{cos }}{{phi }}}right),$$
(9)
where δs is the solar declination, which varies between −23.4° and 23.4° with season and latitude23. Sunset azimuth is the positive and sunrise azimuth is the negative solution to Eq. (9) (relative to geographic N–S).Fixed sun-compass headings represent a uniform (clockwise) offset, ({bar{{{{{{rm{alpha }}}}}}}}_{{mathrm {s}}}) to sunrise or sunset azimuth, θs,i (calculated using Eq. (9))$${{bar{{{{{{rm{alpha }}}}}}}}_{i}={bar{{{{{{rm{alpha }}}}}}}}_{{mathrm {s}}}+theta }_{{mathrm {s}},i}$$
(10)
where the preferred heading on commencement of migration, ({bar{{{{{{rm{alpha }}}}}}}}_{{mathrm {s}}}={bar{{{{{{rm{alpha }}}}}}}}_{0}-{theta }_{{mathrm {s}},0}), is presumed to be imprinted using an inherited geographic or geomagnetic heading2,10,30.With a TCSC, preferred headings relative to sun azimuth are adjusted according to the time of day. In the context of sun-compass use during migration, Alerstam and Pettersson22 related the hourly “clock-shift” induced by crossing bands of longitude (∆h = 12 ∆λ/π), to a migrant’s time-compensated adjustment given the rate of change (i.e., angular speed) of sun azimuth close to sunset$$frac{partial {theta }_{{mathrm {s}}}}{partial h}cong frac{2pi {{sin }}{{phi }}}{24},$$
(11)
resulting in a “time-compensated” offset in heading on departure ((varDelta bar{{{{{{rm{alpha }}}}}}}cong varDelta {{{{{rm{lambda }}}}}},sin phi), which Eq.(4)). Equation (4) results in near-great-circle trajectories for small ranges in latitude, ∅, until inner clocks are reset. The feasibility of TCSC courses over longer distances (latitude ranges) relies on two critical but little-explored assumptions: (1) time-compensated orientation adjustments are presumed to follow the angular speed of sun azimuth (Eq. (11)) retained from the most recent clock-reset site, and (2) to negotiate unpredictable migratory schedules, migrants are presumed to retain their preferred geographic heading on arrival at extended stopovers22.Regarding the first assumption, time-compensated adjustments could also be influenced by proximate speeds of sun azimuth even when inner clocks are not fully reset. We, therefore, use distinct indices to keep track of “reference” flight-steps for clock-resets (cref,i) and time-compensated adjustments (sref,i). TCSC flight-step headings can then be written as$${bar{{{{{{rm{alpha }}}}}}}}_{i}=left{begin{array}{cc}{bar{{{{{{rm{alpha }}}}}}}}_{{c}_{{{mathrm {ref}}},i}}+left({theta }_{{mathrm {s}},i}-{theta }_{{mathrm {s}},{c}_{{{mathrm {ref}}},i}}right)+left({{{{{{rm{lambda }}}}}}}_{i}-{{{{{{rm{lambda }}}}}}}_{{c}_{{{mathrm {ref}}},i}}right){{sin }}{phi }_{{s}_{{{mathrm {ref}}},i}}, & {i,ne, c}_{{{mathrm {ref}}},i} ; (12a)\ {{{{{{rm{alpha }}}}}}}_{i-1}, & {i=c}_{{{mathrm {ref}}},i} ; (12b)end{array}right.,$$where θs,i represents the sunset azimuth on departures, cref,i specifies the most recent clock-reset site (during which geographic headings are also retained, i.e., ({bar{{{{{{rm{alpha }}}}}}}}_{i}={{{{{{rm{alpha }}}}}}}_{i-1})), and sref,i specifies the site defining the migrant’s temporal (hourly) rate of “time-compensated” adjustments (Eq. (11)). For TCSC courses as conceived by Alerstam and Pettersson22, reference rates of adjustment to sun azimuth are reset in tandem during stopovers, i.e., ({s}_{{{mathrm {ref}}},i}={c}_{{{mathrm {ref}}},i}), but we also considered a proximately gauged TCSC, where migrants gauge their adjustments to currently experienced speed of sun azimuth, i.e., ({s}_{{{mathrm {ref}}},i}=i).Regarding the second assumption, retaining geographic headings on arrival at stopovers is not consistent with ignoring geographic headings between consecutive nightly flight-steps, and may be difficult to achieve while landing. We, therefore, examined a more parsimonious alternative (Fig. 7d, Supplementary Fig. 3) where migrants retain their (usual) TCSC heading from the first night of stopovers, i.e., as if they would have departed on the first night. This alternative also simplifies Eq. (12) to$${bar{{{{{{rm{alpha }}}}}}}}_{i}={bar{{{{{{rm{alpha }}}}}}}}_{{c}_{{{mathrm {ref}}},i}}+left({theta }_{{mathrm {s}},({t}_{i-1}+1)}-{theta }_{{mathrm {s}},{t}_{i-1}}right)+left({{{{{{rm{lambda }}}}}}}_{i}-{{{{{{rm{lambda }}}}}}}_{{c}_{{{mathrm {ref}}},i}}right){{sin }}{{{phi }}}_{{s}_{{{mathrm {ref}}},i}}$$
(12c)
where the index ti−1 here represents the departure date from the previous flight.Sensitivity of compass-course headingsSensitivity was assessed by the marginal change in expected heading from previous (imprecise) headings, (partial {bar{alpha }}_{i}/partial {alpha }_{i-1}). When this is positive, small errors in headings will perpetuate, and therefore expected errors in migratory trajectories will grow iteratively. Conversely, negative sensitivity implies self-correction between successive flight-steps. Geographic and geomagnetic loxodromes are per definition constant relative to their respective axes so have “zero” sensitivity, as long as cue-detection errors are stochastically independent.For magnetoclinic compass courses in a dipole field, sensitivity can be calculated by differentiating Eq. (8) with respect to previous headings:$$frac{{mathrm {d}}{bar{{{{{{rm{alpha }}}}}}}}_{i}}{{mathrm {d}}{{{{{{rm{alpha }}}}}}}_{i-1}}=frac{{sin bar{{{{{{rm{alpha }}}}}}}}_{0}}{tan {phi }_{{mathrm {m}},0}}cdot frac{1}{cos {bar{alpha }}_{i}{cos }^{2}{phi }_{{mathrm {m}},i}}frac{partial {phi }_{{mathrm {m}},i}}{partial {alpha }_{i-1}}=frac{{R}_{{mathrm {step}}},sin {alpha }_{i-1}{sin bar{{{{{{rm{alpha }}}}}}}}_{0}}{cos {bar{alpha }}_{i}{cos }^{2}{phi }_{{mathrm {m}},i},tan {phi }_{{mathrm {m}},0}}$$
(13)
All three terms in the denominator indicate, as illustrated in Fig. 3b, that magnetoclinic courses become unstably sensitive at both high and low latitudes, and any heading with a significantly East–West component.Sensitivity of fixed sun compass headings is non-zero due to sun azimuth dependence on location (Eq. (9)):$$frac{{mathrm {d}}{bar{{{{{{rm{alpha }}}}}}}}_{i}}{{mathrm {d}}{{{{{{rm{alpha }}}}}}}_{i-1}} = , frac{sin {delta }_{{mathrm {s}},i}}{sin {theta }_{{mathrm {s}},i}}cdot frac{sin {phi }_{i}}{{cos }^{2}{phi }_{i}}frac{partial {phi }_{i}}{partial {alpha }_{i-1}}=frac{sin {delta }_{{mathrm {s}},i}}{sin {theta }_{{mathrm {s}},i}}cdot frac{{R}_{{mathrm {step}}},sin {phi }_{i},sin {alpha }_{i-1}}{{cos }^{2}{phi }_{i}}\ = , {R}_{{mathrm {step}}}cdot ,sin {alpha }_{i-1}frac{tan {phi }_{i}}{tan {theta }_{{mathrm {s}},i}}$$
(14)
The sine factor on the right-hand side in Eq. (14) causes the sign of (partial {bar{alpha }}_{i}/partial {alpha }_{i-1}) to be opposite for East to West or West to East headings, and tan θs also change sign at the fall equinox (due to solar declination changing sign). The azimuth term in the denominator indicates heightened sensitivity closer to the summer or winter equinox and at high latitudes, and, conversely, heightened robustness to errors closer to the spring or autumnal equinox (since ({{tan }}{theta }_{{mathrm {s}},0}to pm infty)). This seasonal and directional asymmetry is illustrated in Fig. 3c, e.TCSC courses (Eq. (12)) involve up to three sensitivity terms, due to dependencies on sun azimuth, longitude and latitude:$$ frac{{mathrm {d}}{bar{{{{{{rm{alpha }}}}}}}}_{i}}{{mathrm {d}}{{{{{{rm{alpha }}}}}}}_{i-1}} = , {R}_{{{mathrm {step}}}}cdot {{sin }}{alpha }_{i-1}frac{{{tan }}{phi }_{i}}{{{tan }}{theta }_{{mathrm {s}},i}}+frac{{mathrm {d}}{lambda }_{i}}{{mathrm {d}}{{{{{{rm{alpha }}}}}}}_{i-1}}{{sin }}{{{phi }}}_{{c}_{{{mathrm {ref}}}},i}+left({{{{{{rm{lambda }}}}}}}_{i}-{{{{{{rm{lambda }}}}}}}_{{c}_{{{mathrm {ref}}}},i}right)frac{{mathrm {d}}{{sin }}{phi }_{{s}_{{{mathrm {ref}}}},i}}{{mathrm {d}}{{{{{{rm{alpha }}}}}}}_{i-1}}\ =, left{begin{array}{cc}{R}_{{{mathrm {step}}}}cdot left[{{sin }}{alpha }_{i-1}frac{{{tan }}{phi }_{i}}{{{tan }}{theta }_{{mathrm {s}},i}}-frac{{{cos }}{{{{{{rm{alpha }}}}}}}_{i-1}{{sin }}{phi }_{{s}_{{{mathrm {ref}}}},i}}{{{cos }}{phi }_{i-1}}right],hfill & {{{{{rm{classic}}}}}} ; (15{{{{{rm{a}}}}}})\ {R}_{{{mathrm {step}}}}left[{{sin }}{alpha }_{i-1}frac{{{tan }}{phi }_{i}}{{{tan }}{theta }_{{mathrm {s}},i}}-frac{{{cos }}{{{{{{rm{alpha }}}}}}}_{i-1}{{sin }}{phi }_{{s}_{{{mathrm {ref}}}},i}}{{{cos }}{phi }_{i-1}}+left({{{{{{rm{lambda }}}}}}}_{i}-{{{{{{rm{lambda }}}}}}}_{{c}_{{{mathrm {ref}}}},i}right){{sin }}{alpha }_{i-1}{{cos }}{phi }_{i}right], & {{{{{rm{proximate}}}}}} ; left(15{{{{{rm{b}}}}}}right).end{array}right.$$The first square-bracketed terms in Eqs. (15a, b) are identical to the fixed sun compass (Eq. (14)), reflecting seasonal and latitudinal dependence in sun-azimuth. For headings with a Southward component (α0  1) and nonexistent for North–South headings (G = 1, reflecting no longitude bands being crossed). We expected this factor to affect compass courses differentially according to their error-accumulating or self-correcting nature.We further modified the effective goal-area breadth to account for a (geographically) circular goal area on the sphere, i.e., effectively modulating the longitudinal component of the goal-area breadth at the arrival latitude, ∅A:$${beta }_{{mathrm {A}}}=beta sqrt{{{{{sin }}}^{2}bar{alpha }+left({{cos }}bar{alpha }/{{cos }}{{{phi }}}_{{mathrm {A}}}right)}^{2}}.$$
(19)
To account for differential sensitivity among compass-courses, we generalized the normal many-wrongs relation between performance and number of steps, (1/{hat{N}}^{eta }), from η = 0.5 (Eqs. (3) and (16)) to$$eta left({sigma }_{{step}}|s,bright)=left(0.5+bright){e}^{-s{{sigma }_{{step}}}^{2}},$$
(20)
where b  0 self-correction, and s represents a modulating exponential damping factor, consistent with the limiting circular-uniform case (as κ → 0, i.e., ({sigma }_{{{mathrm {step}}}}to infty)), where no (timely) convergence of heading is expected with an increasing number of steps.In assessing performance, we also accounted for seasonal migration constraints via a population-specific maximum number of steps, Nmax (Table 2; this became significant for the longest-distance simulations with large expected errors, i.e., small ({{{{{{rm{kappa }}}}}}}_{{{mathrm {step}}}}=1/{sigma }_{{{mathrm {step}}}}^{2})). The probability of having arrived at the goal latitude can be estimated using the Central Limit Theorem:$${p}_{{{phi }},{N}_{{max }}}cong frac{1}{2}left[1-{erf}left(left(frac{{N}_{0}}{{N}_{{max }}}-frac{{I}_{1}left({{{{{{rm{kappa }}}}}}}_{{{mathrm {step}}}}right)}{{I}_{0}left({{{{{{rm{kappa }}}}}}}_{{{mathrm {step}}}}right)}right)cdot frac{{{cos }}bar{alpha }}{{sigma }_{{mathrm {C}}}sqrt{2}}right)right],$$
(21)
where Ij is the modified Bessel function of the first kind and order j53, and σC (the standard deviation in the latitudinal component of flight-step distance) can be calculated using Bessel functions together with known properties of sums of cosines53,77 (Supplementary Note 2).Regression-estimated performanceWe fit the parameters in the spherical-geometry factor (Eq. (18)) and many-wrongs effect (Eq. (20)) according to expected performance, estimated as the product of sufficiently timely migration (Eq. (21)) and sufficiently precise migration, now generalized from Eq. (16), i.e.$${p}_{beta ,hat{N}}cong {erf}left(frac{{beta }_{{mathrm {A}}}}{{G}^{{g}}sqrt{2left({{sigma }_{{{mathrm {ind}}}}}^{2}+{sigma }_{{{mathrm {step}}}}/{hat{N}}^{n}right)}}right),$$
(22)
This resulted in up to four fitted parameters for each compass course

i.

an exponent, g, to the spherical-geometry factor (Eq. (19)), i.e., Gg, reflecting how growth or self-correction in errors between steps further augments or reduces this factor,

ii.

a baseline offset, b0, to the “normal” exponent η = 0.5, which mediates the relation between the number of steps and performance (Eq. (20)),

iii.

an exponent s reflecting how decreasing precision among flight-steps dampens the many-wrongs convergence (Eq. (20)),

iv.

for TCSC courses, a modulation, ρ, to the offset, b0, quantifying the extent to which self-correction increases with increased flight-step distance Rstep, i.e., ({{b={b}_{0}R}_{{{mathrm {step}}}}^{{prime} }}^{rho }) in Eq. (20), where ({R}_{{{mathrm {step}}}}^{{prime} })is the flight-step distance scaled by its median value among species.

Parameters were fit using MATLAB routine fitnlm based on compass course performance among species and seven error scenarios (5°, 10°, 20°, 30°, 40°, 50°, and 60° directional precision among flight-steps), for all combinations (including or excluding the four parameters). The most parsimonious combination of parameters was selected using MATLAB routine aicbic, based on the AICc, the Akaike information criterion corrected for small sample size57. Null values for the spherical-geometry parameter were set to g = 1, and for the parameters governing convergence of route-mean headings b0 = 0, s = 0, and, for TCSC courses, ρ = 0 (for loxodrome courses, ρ = 0 by default, i.e., was not fitted).Statistics and reproducibilityOur simulation results, regression fitting and AICc-model selection are reproducible using the MATLAB scripts (see the section “Code availability”).Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Arias, P. A. et al. Technical summary. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (2021).Pinsky, M. L., Eikeset, A. M., McCauley, D. J., Payne, J. L. & Sunday, J. M. Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature 569, 108–111 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Sunday, J. M., Bates, A. E. & Dulvy, N. K. Thermal tolerance and the global redistribution of animals. Nat. Clim. Chang. 2, 686–690 (2012).ADS 
Article 

Google Scholar 
Fry, F. Effects of the environment on animal activity. Publ. Ontario Fish. Res. Lab. 55, 1–62 (1947).
Google Scholar 
Lutterschmidt, W. I. & Hutchison, V. H. The critical thermal maximum: history and critique. Can. J. Zool. 75, 1561–1574, https://doi.org/10.1139/z97-783 (2011).Article 

Google Scholar 
Rezende, E. L., Castañeda, L. E. & Santos, M. Tolerance landscapes in thermal ecology. Funct. Ecol. 28, 799–809 (2014).Article 

Google Scholar 
Bozinovic, F., Calosi, P. & Spicer, J. I. Physiological correlates of geographic range in animals. Annu. Rev. Ecol. Evol. S. 42, 155–179 (2011).Article 

Google Scholar 
Sunday, J. M. et al. Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation. Proc. Natl. Acad. Sci. USA 111, 5610–5615 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl. Acad. Sci. USA 105, 6668–6672 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Comte, L. & Olden, J. D. Climatic vulnerability of the world’s freshwater and marine fishes. Nat. Clim. Chang. 7, 718–722 (2017).ADS 
Article 

Google Scholar 
Dahlke, F. T., Wohlrab, S., Butzin, M. & Pörtner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Pottier, P., Burke, S., Drobniak, S. M. & Nakagawa, S. Methodological inconsistencies define thermal bottlenecks in fish life cycle: a comment on Dahlke et al. 2020. Evol. Ecol. 36, 287–292 (2022).Article 

Google Scholar 
Dahlke, F., Butzin, M., Wohlrab, S. & Pörtner, H.-O. Reply to: methodological inconsistencies define thermal bottlenecks in fish life cycle. Evol. Ecol. 36, 293–298 (2022).Article 

Google Scholar 
Pottier, P. et al. Developmental plasticity in thermal tolerance: Ontogenetic variation, persistence, and future directions. Ecol. Lett. (2022).Morley, S. A., Peck, L. S., Sunday, J. M., Heiser, S. & Bates, A. E. Physiological acclimation and persistence of ectothermic species under extreme heat events. Glob. Ecol. Biogeogr. 28, 1018–1037 (2019).Article 

Google Scholar 
Rohr, J. R. et al. The complex drivers of thermal acclimation and breadth in ectotherms. Ecol. Lett. 21, 1425–1439 (2018).PubMed 
Article 

Google Scholar 
Gunderson, A. R. & Stillman, J. H. Plasticity in thermal tolerance has limited potential to buffer ectotherms from global warming. Proc. R. Soc. B-Biol. Sci. 282, 20150401 (2015).Article 

Google Scholar 
Weaving, H., Terblanche, J. S., Pottier, P. & English, S. Meta-analysis reveals weak but pervasive plasticity in insect thermal limits. Nat. Commun. 13, 1–11 (2022).Article 

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

Google Scholar 
Bennett, J. M. et al. The evolution of critical thermal limits of life on Earth. Nat. Commun. 12, 1198 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
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).Article 

Google Scholar 
Kellermann, V. et al. Upper thermal limits of Drosophila are linked to species distributions and strongly constrained phylogenetically. Proc. Natl. Acad. Sci. USA 109, 16228–16233 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Morgan, R., Finnøen, M. H., Jensen, H., Pélabon, C. & Jutfelt, F. Low potential for evolutionary rescue from climate change in a tropical fish. Proc. Natl. Acad. Sci. USA 117, 33365–33372 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bennett, J. M. et al. GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms. Sci. Data 5, 180022 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Leiva, F. P., Calosi, P. & Verberk, W. C. E. P. Scaling of thermal tolerance with body mass and genome size in ectotherms: a comparison between water- and air-breathers. Philos. Trans. R. Soc. B-Biol. Sci. 374, 20190035 (2019).Article 

Google Scholar 
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 
Article 

Google Scholar 
Nakagawa, S. & Freckleton, R. P. Missing inaction: the dangers of ignoring missing data. Trends Ecol. Evol. 23, 592–596 (2008).PubMed 
Article 

Google Scholar 
Johnson, T. F., Isaac, N. J. B., Paviolo, A. & González-Suárez, M. Handling missing values in trait data. Glob. Ecol. Biogeogr. 30, 51–62 (2021).Article 

Google Scholar 
Foo, Y. Z., O’Dea, R. E., Koricheva, J., Nakagawa, S. & Lagisz, M. A practical guide to question formation, systematic searching and study screening for literature reviews in ecology and evolution. Methods Ecol. Evol. 12, 1705–1720 (2021).Article 

Google Scholar 
Reboredo Segovia, A. L., Romano, D. & Armsworth, P. R. Who studies where? Boosting tropical conservation research where it is most needed. Front. Ecol. Environ. 18, 159–166 (2020).Article 

Google Scholar 
White, C. R. et al. Geographical bias in physiological data limits predictions of global change impacts. Funct. Ecol. 35, 1572–1578 (2021).Article 

Google Scholar 
Amano, T., González-Varo, J. P. & Sutherland, W. J. Languages are still a major barrier to global Science. PLoS Biol. 14, e2000933 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Bennett, S., Duarte, C. M., Marbà, N. & Wernberg, T. Integrating within-species variation in thermal physiology into climate change ecology. Philos. Trans. R. Soc. B-Biol. Sci. 374, 20180550 (2019).Article 

Google Scholar 
Noble, D. W. A. et al. Meta-analytic approaches and effect sizes to account for ‘nuisance heterogeneity’ in comparative physiology. J. Exp. Biol. 225, jeb243225 (2022).PubMed 
Article 

Google Scholar 
Peralta-Maraver, I. & Rezende, E. L. Heat tolerance in ectotherms scales predictably with body size. Nat. Clim. Chang. 11, 58–63 (2021).ADS 
Article 

Google Scholar 
McKenzie, D. J. et al. Intraspecific variation in tolerance of warming in fishes. J. Fish Biol. 98, 1536–1555 (2021).PubMed 
Article 

Google Scholar 
Morrissey, M. B. Meta-analysis of magnitudes, differences and variation in evolutionary parameters. J. Evol. Biol. 29, 1882–1904 (2016).CAS 
PubMed 
Article 

Google Scholar 
Duffy, G. A., Kuyucu, A. C., Hoskins, J. L., Hay, E. M. & Chown, S. L. Adequate sample sizes for improved accuracy of thermal trait estimates. Funct. Ecol. 35, 2647–2662 (2021).CAS 
Article 

Google Scholar 
IUCN. The IUCN Red List of Threatened Species. https://www.iucnredlist.org (2021).Harfoot, M. B. J. et al. Using the IUCN Red List to map threats to terrestrial vertebrates at global scale. Nat. Ecol. Evol. 5, 1510–1519 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Sodhi, N. K. et al. Measuring the meltdown: Drivers of global amphibian extinction and decline. PLoS One 3 (2008).Nowakowski, A. J. et al. Tropical amphibians in shifting thermal landscapes under land-use and climate change. Conserv. Physiol. 31, 96–105 (2017).
Google Scholar 
Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl. Acad. Sci. USA 110, E2602–E2610 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ouzzani, M., Hammady, H., Fedorowicz, Z. & Elmagarmid, A. Rayyan—a web and mobile app for systematic reviews. Syst. Rev. 5, 210 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Vera-Baceta, M.-A., Thelwall, M. & Kousha, K. Web of Science and Scopus language coverage. Scientometrics 121, 1803–1813 (2019).Article 

Google Scholar 
Giustini, D. & Boulos, M. N. K. Google Scholar is not enough to be used alone for systematic reviews. Online J. Public Health Inform. 5, 214 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Haddaway, N. R., Collins, A. M., Coughlin, D. & Kirk, S. The role of Google Scholar in evidence reviews and its applicability to grey literature searching. PLoS One 10, e0138237 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Gusenbauer, M. & Haddaway, N. R. Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Res. Synth. Methods 11, 181–217 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Harzing, A. Publish or perish. Res. Int. Manag. Softw. Release 27 (2007).Cheng, C.-B. A study of warming tolerance and thermal acclimation capacity of tadpoles in Taiwan. (Tunghai University, 2017).Wu, Q.-H. & Hsieh, C.-H. Thermal tolerance and population genetics of Hynobius fuca. (Chinese Culture University, 2016).Jørgensen, L. B., Malte, H., Ørsted, M., Klahn, N. A. & Overgaard, J. A unifying model to estimate thermal tolerance limits in ectotherms across static, dynamic and fluctuating exposures to thermal stress. Sci. Rep. 11, 1–14 (2021).Article 

Google Scholar 
Agudelo-Cantero, G. A. & Navas, C. A. Interactive effects of experimental heating rates, ontogeny and body mass on the upper thermal limits of anuran larvae. J. Therm. Biol. 82, 43–51 (2019).PubMed 
Article 

Google Scholar 
Alveal Riquelme, N. Relaciones entre la fisiología térmica y las características bioclimáticas de Rhinella spinulosa (Anura: Bufonidae) en Chile a través del enlace mecanicista de nicho térmico. (Universidad de Concepción, 2015).Alves, M. Tolerância térmica em espécies de anuros neotropicais do gênero Dendropsophus Fitzinger, 1843 e efeito da temperatura na resposta à predação. (Universidade Estadual de Santa Cruz, 2016).Anderson, R. C. O. & Andrade, D. V. Trading heat and hops for water: Dehydration effects on locomotor performance, thermal limits, and thermoregulatory behavior of a terrestrial toad. Ecol. Evol. 7, 9066–9075 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Aponte Gutiérrez, A. Endurecimiento térmico en Pristimantis medemi (Anura: Craugastoridae), en coberturas boscosas del Municipio de Villavicencio (Meta). (Universidad Nacional de Colombia, 2020).Arrigada García, K. Conductas térmica en dos poblaciones de Batrachyla taeniata provenientes de la localidad de Ucúquer en la región de O’Higgins y de la localidad de Hualpén en la región del Bío-Bío (Universidad de Concepción, 2019).Azambuja, G., Martins, I. K., Franco, J. L. & Santos, T. Gdos Effects of mancozeb on heat shock protein 70 (HSP70) and its relationship with the thermal physiology of Physalaemus henselii (Peters, 1872) tadpoles (Anura: Leptodactylidae). J. Therm. Biol. 98, 102911 (2021).CAS 
PubMed 
Article 

Google Scholar 
Bacigalupe, L. D. et al. Natural selection on plasticity of thermal traits in a highly seasonal environment. Evol. Appl. 11, 2004–2013 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Barria, A. M. & Bacigalupe, L. D. Intraspecific geographic variation in thermal limits and acclimatory capacity in a wide distributed endemic frog. J. Therm. Biol. 69, 254–260 (2017).PubMed 
Article 

Google Scholar 
Beltrán, I., Ramírez-Castañeda, V., Rodríguez-López, C., Lasso, E. & Amézquita, A. Dealing with hot rocky environments: critical thermal maxima and locomotor performance in Leptodactylus lithonaetes (anura: Leptodactylidae). Herpetol. J. 29, 155–161 (2019).Article 

Google Scholar 
Berkhouse, C. & Fries, J. Critical thermal maxima of juvenile and adult San Marcos salamanders (Eurycea nana). Southwest. Nat. 40, 430–434 (1995).
Google Scholar 
Blem, C. R., Ragan, C. A. & Scott, L. S. The thermal physiology of two sympatric treefrogs Hyla cinerea and Hyla chrysoscelis (Anura; Hylidae). Comp. Biochem. Physiol. 85, 563–570 (1986).CAS 
Article 

Google Scholar 
Bonino, M. F., Cruz, F. B. & Perotti, M. G. Does temperature at local scale explain thermal biology patterns of temperate tadpoles? J. Therm. Biol. 94 (2020).Bovo, R. P. Fisiologia térmica e balanço hídrico em anfíbios anuros. (Universidad Estadual Paulista, 2015).Brattstrom, B. H. Thermal acclimation in Australian amphibians. Comp. Biochem. Physiol. 35, 69–103 (1970).Article 

Google Scholar 
Brattstrom, B. H. & Regal, P. Rate of thermal acclimation in the Mexican salamander. Chiropterotriton. Copeia 1965, 514–515 (1965).Article 

Google Scholar 
Brattstrom, B. H. A preliminary review of the thermal requirements of amphibians. Ecology 44, 238–255 (1963).Article 

Google Scholar 
Brattstrom, B. H. Thermal acclimation in anuran amphibians as a function of latitude and altitude. Comp. Biochem. Physiol. 24, 93–111 (1968).CAS 
PubMed 
Article 

Google Scholar 
Brattstrom, B. H. & Lawrence, P. The rate of thermal acclimation in anuran amphibians. Physiol. Zool. 35, 148–156 (1962).Article 

Google Scholar 
Brown, H. A. The heat resistance of some anuran tadpoles (Hylidae and Pelobatidae). Copeia 1969, 138 (1969).Article 

Google Scholar 
Burke, E. M. & Pough, F. H. The role of fatigue in temperature resistance of salamanders. J. Therm. Biol. 1, 163–167 (1976).Article 

Google Scholar 
Burrowes, P. A., Navas, C. A., Jiménez-Robles, O., Delgado, P. & De La Riva, I. Climatic heterogeneity in the Bolivian andes: Are frogs trapped? S. Am. J. Herpetol. 18, 1–12 (2020).Article 

Google Scholar 
Bury, R. B. Low thermal tolerances of stream amphibians in the Pacific Northwest: Implications for riparian and forest management. Appl. Herpetol. 5, 63–74 (2008).Article 

Google Scholar 
Castellanos García, L. A. Days of futures past: Integrating physiology, microenvironments, and biogeographic history to predict response of frogs in neotropical dry-forest to global warming. (Universidad de los Andes, 2017).Castro, B. Influence of environment on thermal ecology of direct-developing frogs (Anura: Craugastoridae: Pristimantis) in the eastern Andes of Colombia. (Universidad de los Andes, 2019).Catenazzi, A., Lehr, E. & Vredenburg, V. T. Thermal physiology, disease, and amphibian declines on the eastern slopes of the Andes. Conserv. Biol. 28, 509–517 (2014).PubMed 
Article 

Google Scholar 
Chang, L.-W. Heat tolerance and its plasticity in larval Bufo bankorensis from different altitudes. (National Cheng Kung University, 2002).Chavez Landi, P. A. Fisiología térmica de un depredador Dasythemis sp. (Odonata: Libellulidae) y su presa Hypsiboas pellucens (Anura: Hylidae) y sus posibles implicaciones frente al cambio climático. (Pontificia Universidad Católica Del Ecuador, 2017).Chen, T.-C., Kam, Y.-C. & Lin, Y.-S. Thermal physiology and reproductive phenology of Buergeria japonica (Rhacophoridae) breeding in a stream and a geothermal hotspring in Taiwan. Zool. Sci. 18, 591–596 (2001).Article 

Google Scholar 
Cheng, Y.-J. Effect of salinity on the critical thermal maximum of tadpoles living in brackish water. (Tunghai University, 2017).Christian, K. A., Nunez, F., Clos, L. & Diaz, L. Thermal relations of some tropical frogs along an altitudinal gradient. Biotropica 20, 236–239 (1988).Article 

Google Scholar 
Claussen, D. L. The thermal relations of the tailed frog, Ascaphus truei, and the pacific treefrog, Hyla regilla. Comp. Biochem. Physiol. 44, 137–153 (1973).Article 

Google Scholar 
Claussen, D. L. Thermal acclimation in ambystomatid salamanders. Comp. Biochem. Physiol. 58, 333–340 (1977).Article 

Google Scholar 
Contreras Cisneros, J. Temperatura crítica máxima, tolerancia al frío y termopreferendum del tritón del Montseny (Calotriton arnoldii). (Universitat de Barcelona, 2019).Contreras Oñate, S. Posible efecto de las temperaturas de aclimatación sobre las respuestas térmicas en temperaturas críticas máximas (TCmás) y mínimas (TCmín) de una población de Batrachyla taeniata (Universidad de Concepción, 2016).Cooper, R. D. & Shaffer, H. B. Allele-specific expression and gene regulation help explain transgressive thermal tolerance in non-native hybrids of the endangered California tiger salamander (Ambystoma californiense). Mol. Ecol. 30, 987–1004 (2021).CAS 
PubMed 
Article 

Google Scholar 
Crow, J. C., Forstner, M. R. J., Ostr, K. G. & Tomasso, J. R. The role of temperature on survival and growth of the barton springs salamander (Eurycea sosorum). Herpetol. Conserv. Biol. 11, 328–334 (2016).
Google Scholar 
Cupp, P. V. Thermal tolerance of five salientian amphibians during development and metamorphosis. Herpetologica 36, 234–244 (1980).
Google Scholar 
Dabruzzi, T. F., Wygoda, M. L. & Bennett, W. A. Some like it hot: Heat tolerance of the crab-eating frog, Fejervarya cancrivora. Micronesica 43, 101–106 (2012).
Google Scholar 
Dainton, B. H. Heat tolerance and thyroid activity in developing tadpoles and juvenile adults of Xenopus laevis (Daudin). J. Therm. Biol. 16, 273–276 (1991).Article 

Google Scholar 
Daniel, N. J. J. Impact of climate change on Singapore amphibians. (National University of Singapore, 2013).Davies, S. J., McGeoch, M. A. & Clusella-Trullas, S. Plasticity of thermal tolerance and metabolism but not water loss in an invasive reed frog. Comp. Biochem. Physiol. 189, 11–20 (2015).CAS 
Article 

Google Scholar 
de Oliviera Anderson, R. C., Bovo, R. P. & Andrade, D. V. Seasonal variation in the thermal biology of a terrestrial toad, Rhinella icterica (Bufonidae), from the Brazilian Atlantic Forest. J. Therm. Biol. 74, 77–83 (2018).Article 

Google Scholar 
de Vlaming, V. L. & Bury, R. B. Thermal selection in tadpoles of the tailed-frog. Ascaphus truei. J. Herpetol. 4, 179–189 (1970).Article 

Google Scholar 
Delson, J. & Whitford, W. G. Critical thermal maxima in several life history stages in desert and montane populations of Ambystoma tigrinum. Herpetologica 29, 352–355 (1973).
Google Scholar 
Duarte, H. et al. Can amphibians take the heat? Vulnerability to climate warming in subtropical and temperate larval amphibian communities. Glob. Chang. Biol. 18, 412–421 (2012).ADS 
Article 

Google Scholar 
Duarte, H. S. A comparative study of the thermal tolerance of tadpoles of Iberian anurans. (Universidade de Lisboa, 2011).Dunlap, D. Evidence for a daily rhythm of heat resistance in cricket frogs, Acris crepitans. Copeia. 4, 852–854 (1969).Article 

Google Scholar 
Dunlap, D. G. Critical thermal maximum as a function of temperature of acclimation in two species of hylid frogs. Physiol. Zool. 41, 432–439 (1968).Article 

Google Scholar 
Elwood, J. R. L. Variation in hsp70 levels and thermotolerance among terrestrial salamanders of the Plethodon glutinosus complex. (Drexel University, 2003).Enriquez-Urzelai, U. et al. Ontogenetic reduction in thermal tolerance is not alleviated by earlier developmental acclimation in Rana temporaria. Oecologia 189, 385–394 (2019).ADS 
PubMed 
Article 

Google Scholar 
Enriquez-Urzelai, U. et al. The roles of acclimation and behaviour in buffering climate change impacts along elevational gradients. J. Anim. Ecol. 89, 1722–1734 (2020).PubMed 
Article 

Google Scholar 
Erskine, D. J. & Hutchison, V. H. Reduced thermal tolerance in an amphibian treated with melatonin. J. Therm. Biol. 7, 121–123 (1982).CAS 
Article 

Google Scholar 
Escobar Serrano, D. Acclimation scope of the critical thermal limits in Agalychnis spurrelli (Hylidae) and Gastrotheca pseustes (Hemiphractidae) and their implications under climate change scenarios. (Pontificia Universidad Católica Del Ecuador, 2016).Fan, X., Lei, H. & Lin, Z. Ontogenetic shifts in selected body temperature and thermal tolerance of the tiger frog. Hoplobatrachus chinensis. Acta Ecol. Sin. 32, 5574–5580 (2012).
Google Scholar 
Fan, X. L., Lin, Z. H. & Scheffers, B. R. Physiological, developmental, and behavioral plasticity in response to thermal acclimation. J. Therm. Biol. 97 (2021).Fernández-Loras, A. et al. Infection with Batrachochytrium dendrobatidis lowers heat tolerance of tadpole hosts and cannot be cleared by brief exposure to CTmax. PLoS ONE 14 (2019).Floyd, R. B. Ontogenetic change in the temperature tolerance of larval Bufo marinus (Anura: bufonidae). Comp. Biochem. Physiol. 75, 267–271 (1983).Article 

Google Scholar 
Floyd, R. B. Effects of photoperiod and starvation on the temperature tolerance of larvae of the giant toad, Bufo marinus. Copeia 1985, 625–631 (1985).MathSciNet 
Article 

Google Scholar 
Fong, S.-T. Thermal tolerance of adult Asiatic painted frog Kaloula pulchra from different populations. (National University of Tainan, 2014).Frishkoff, L. O., Hadly, E. A. & Daily, G. C. Thermal niche predicts tolerance to habitat conversion in tropical amphibians and reptiles. Glob. Chang. Biol. 21, 3901–3916 (2015).ADS 
PubMed 
Article 

Google Scholar 
Frost, J. S. & Martin, E. W. A comparison of distribution and high temperature tolerance in Bufo americanus and Bufo woodhousii fowleri. Copeia 1971, 750 (1971).Article 

Google Scholar 
Gatz, A. J. Critical thermal maxima of Ambystoma maculatum (Shaw) and Ambystoma jeffersonianum (Green) in relation to time of breeding. Herpetologica 27, 157–160 (1971).
Google Scholar 
Gatz, A. J. Intraspecific variations in critical thermal maxima of Ambystoma maculatum. Herpetologica 29, 264–268 (1973).
Google Scholar 
Geise, W. & Linsenmair, K. E. Adaptations of the reed frog Hyperolius viridiflavus (Amphibia, Anura, Hyperoliidae) to its arid environment – IV. Ecological significance of water economy with comments on thermoregulation and energy allocation. Oecologia 77, 327–338 (1988).ADS 
CAS 
PubMed 
Article 

Google Scholar 
González-del-Pliego, P. et al. Thermal tolerance and the importance of microhabitats for Andean frogs in the context of land use and climate change. J. Anim. Ecol. 89, 2451–2460 (2020).PubMed 
Article 

Google Scholar 
Gouveia, S. F. et al. Climatic niche at physiological and macroecological scales: The thermal tolerance-geographical range interface and niche dimensionality. Glob. Ecol. Biogeogr. 23, 446–456 (2014).Article 

Google Scholar 
Gray, R. Lack of physiological differentiation in three color morphs of the cricket frog (Acris crepitans) in Illinois. Trans. Ill. State Acad. Sci. 70, 73–79 (1977).ADS 

Google Scholar 
Greenspan, S. E. et al. Infection increases vulnerability to climate change via effects on host thermal tolerance. Sci. Rep. 7 (2017).Guevara-Molina, E. C., Gomes, F. R. & Camacho, A. Effects of dehydration on thermoregulatory behavior and thermal tolerance limits of Rana catesbeiana (Shaw, 1802). J. Therm. Biol. 93 (2020).Gutiérrez Pesquera, L. Una valoración macrofisiológica de la vulnerabilidad al calentamiento global. Análisis de los límites de tolerancia térmica en comunidades de anfibios en gradients latitudinales y altitudinales. (Pontificia Universidad Católica Del Ecuador, 2015).Gutiérrez Pesquera, M. Thermal tolerance across latitudinal and altitudinal gradients in tadpoles. (Universidad de Sevilla, 2016).Gutiérrez-Pesquera, L. M. et al. Testing the climate variability hypothesis in thermal tolerance limits of tropical and temperate tadpoles. J. Biogeogr. 43, 1166–1178 (2016).Article 

Google Scholar 
Gvoždík, L., Puky, M. & Šugerková, M. Acclimation is beneficial at extreme test temperatures in the Danube crested newt, Triturus dobrogicus (Caudata, Salamandridae). Bio. J. Linn. Soc. 90, 627–636 (2007).Article 

Google Scholar 
Heatwole, H., De Austin, S. B. & Herrero, R. Heat tolerances of tadpoles of two species of tropical anurans. Comp. Biochem. Physiol. 27, 807–815 (1968).Article 

Google Scholar 
Heatwole, H., Mercado, N. & Ortiz, E. Comparison of critical thermal maxima of two species of Puerto Rican frogs of the genus. Eleutherodactylus. Physiol. Zool. 38, 1–8 (1965).Article 

Google Scholar 
Holzman, N. & McManus, J. J. Effects of acclimation on metabolic rate and thermal tolerance in the carpenter frog. Rana vergatipes. Comp. Biochem. Physiol. 45, 833–842 (1973).CAS 
Article 

Google Scholar 
Hoppe, D. M. Thermal tolerance in tadpoles of the chorus frog Pseudacris triseriata. Herpetologica 34, 318–321 (1978).
Google Scholar 
Hou, P.-C. Thermal tolerance and preference in the adult amphibians from different altitudinal LTER sites. (National Cheng Kung University, 2003).Howard, J. H., Wallace, R. L. & Stauffer, J. R. Jr Critical thermal maxima in populations of Ambystoma macrodactylum from different elevations. J. Herpetol. 17, 400–402 (1983).Article 

Google Scholar 
Hutchison, V. H. & Ritchart, J. P. Annual cycle of thermal tolerance in the salamander. Necturus maculosus. J. Herpetol. 23, 73–76 (1989).Article 

Google Scholar 
Hutchison, V. H. The distribution and ecology of the cave salamander, Eurycea lucifuga. Ecol. Monogr. 28, 2–20 (1958).Article 

Google Scholar 
Hutchison, V. H. Critical thermal maxima in salamanders. Physiol. Zool. 34, 92–125 (1961).Article 

Google Scholar 
Hutchison, V. H., Engbretson, G. & Turney, D. Thermal acclimation and tolerance in the hellbender, Cryptobranchus alleganiensis. Copeia 1973, 805–807 (1973).Article 

Google Scholar 
Hutchison, V. H. & Rowlan, S. D. Thermal acclimation and tolerance in the mudpuppy. Necturus maculosus. J. Herpetol. 9, 367–368 (1975).Article 

Google Scholar 
Jiang, S., Yu, P. & Hu, Q. A study on the critical thermal maxima of five species of salamanders of China. Acta Herpetol. Sin. 6, 56–62 (1987).
Google Scholar 
John-Alder, H. B., Morin, P. J. & Lawler, S. Thermal physiology, phenology, and distribution of tree frogs. Am. Nat. 132, 506–520 (1988).Article 

Google Scholar 
Johnson, C. R. Daily variation in the thermal tolerance of Litoria caerulea (Anura: Hylidae). Comp. Biochem. Physiol. 40, 1109–1111 (1971).Article 

Google Scholar 
Johnson, C. R. Thermal relations and water balance in the day frog, Taudactylus diurnus, from an Australian rain forest. Aust. J. Zool. 19, 35–39 (1971).Article 

Google Scholar 
Johnson, C. R. Diel variation in the thermal tolerance of Litoria gracilenta (Anura: Hylidae). Comp. Biochem. Physiol. 41, 727–730 (1972).CAS 
Article 

Google Scholar 
Johnson, C. R. & Prine, J. E. The effects of sublethal concentrations of organophosphorus insecticides and an insect growth regulator on temperature tolerance in hydrated and dehydrated juvenile western toads. Bufo boreas. Comp. Biochem. Physiol. 53, 147–149 (1976).CAS 
Article 

Google Scholar 
Johnson, C. R. Observations on body temperatures, critical thermal maxima and tolerance to water loss in the Australian hylid, Hyla caerulea (White). Proc. R. Soc. Qld. 82, 47–50 (1970).
Google Scholar 
Johnson, C. R. Thermal relations and daily variation in the thermal tolerance in. Bufo marinus. J. Herpetol. 6, 35 (1972).Article 

Google Scholar 
Johnson, C. Thermal relations in some southern and eastern Australian anurans. Proc. R. Soc. Qld. 82, 87–94 (1971).
Google Scholar 
Johnson, C. The effects of five organophosphorus insecticides on thermal stress in tadpoles of the Pacific tree frog. Hyla regilla. Zool. J. Linn. Soc. 69, 143–147 (1980).ADS 
Article 

Google Scholar 
Katzenberger, M., Duarte, H., Relyea, R., Beltrán, J. F. & Tejedo, M. Variation in upper thermal tolerance among 19 species from temperate wetlands. J. Therm. Biol. 96 (2021).Katzenberger, M. et al. Swimming with predators and pesticides: How environmental stressors affect the thermal physiology of tadpoles. PLoS ONE 9 (2014).Katzenberger, M., Hammond, J., Tejedo, M. & Relyea, R. Source of environmental data and warming tolerance estimation in six species of North American larval anurans. J. Therm. Biol. 76, 171–178 (2018).PubMed 
Article 

Google Scholar 
Katzenberger, M. Thermal tolerance and sensitivity of amphibian larvae from Palearctic and Neotropical communities. (Universidade de Lisboa, 2013).Katzenberger, M. Impact of global warming in holarctic and neotropical communities of amphibians. (Universidad de Sevilla, 2014).Kern, P., Cramp, R. L. & Franklin, C. E. Temperature and UV-B-insensitive performance in tadpoles of the ornate burrowing frog: An ephemeral pond specialist. J. Exp. Biol. 217, 1246–1252 (2014).PubMed 

Google Scholar 
Kern, P., Cramp, R. L., Seebacher, F., Ghanizadeh Kazerouni, E. & Franklin, C. E. Plasticity of protective mechanisms only partially explains interactive effects of temperature and UVR on upper thermal limits. Comp. Biochem. Physiol. 190, 75–82 (2015).CAS 
Article 

Google Scholar 
Kern, P., Cramp, R. L. & Franklin, C. E. Physiological responses of ectotherms to daily temperature variation. J. Exp. Biol. 218, 3068–3076 (2015).PubMed 

Google Scholar 
Komaki, S., Igawa, T., Lin, S.-M. & Sumida, M. Salinity and thermal tolerance of Japanese stream tree frog (Buergeria japonica) tadpoles from island populations. Herpetol. J. 26, 207–211 (2016).
Google Scholar 
Komaki, S., Lau, Q. & Igawa, T. Living in a Japanese onsen: Field observations and physiological measurements of hot spring amphibian tadpoles. Buergeria japonica. Amphib. Reptil. 37, 311–314 (2016).Article 

Google Scholar 
Krakauer, T. Tolerance limits of the toad, Bufo marinus, in South Florida. Comp. Biochem. Physiol. 33, 15–26 (1970).CAS 
PubMed 
Article 

Google Scholar 
Kurabayashi, A. et al. Improved transport of the model amphibian, Xenopus tropicalis, and its viable temperature for transport. Curr. Herpetol. 33, 75–87 (2014).Article 

Google Scholar 
Lau, E. T. C., Leung, K. M. Y. & Karraker, N. E. Native amphibian larvae exhibit higher upper thermal limits but lower performance than their introduced predator. Gambusia affinis. J. Therm. Biol. 81, 154–161 (2019).PubMed 
Article 

Google Scholar 
Layne, J. R. & Claussen, D. L. Seasonal variation in the thermal acclimation of critical thermal maxima (CTMax) and minima (CTMin) in the salamander. Eurycea bislineata. J. Therm. Biol. 7, 29–33 (1982).Article 

Google Scholar 
Layne, J. R. & Claussen, D. L. The time courses of CTMax and CTMin acclimation in the salamander. Desmognathus fuscus. J. Therm. Biol. 7, 139–141 (1982).Article 

Google Scholar 
Lee, P.-T. Acidic effect on tadpoles living in container habitats. (Tunghai University, 2019).Longhini, L. S., De Almeida Prado, C. P., Bícego, K. C., Zena, L. A. & Gargaglioni, L. H. Measuring cardiorespiratory variables on small tadpoles using a non-invasive methodology. Rev. Cuba. Investig. Biomed. 38 (2019).López Rosero, A. C. Ontogenetic variation of thermal tolerance in two anuran species of Ecuador: Gastrotheca pseustes (Hemiphractidae) and Smilisca phaeota (Hylidae) and their relative vulnerability to environmental temperature change. (Pontificia Universidad Católica Del Ecuador, 2015).Lotshaw, D. P. Temperature adaptation and effects of thermal acclimation in Rana sylvatica and Rana catesbeiana. Comp. Biochem. Physiol. 56, 287–294 (1977).Article 

Google Scholar 
Lu, H.-L., Wu, Q., Geng, J. & Dang, W. Swimming performance and thermal resistance of juvenile and adult newts acclimated to different temperatures. Acta Herpetol. 11, 189–195 (2016).
Google Scholar 
Lu, H. L., Geng, J., Xu, W., Ping, J. & Zhang, Y. P. Physiological response and changes in swimming performance after thermal acclimation in juvenile chinese fire-belly newts, Cynops orientalis. Acta Ecol. Sin. 37, 1603–1610 (2017).
Google Scholar 
Lutterschmidt, W. I. & Hutchison, V. H. The critical thermal maximum: Data to support the onset of spasms as the definitive end point. Can. J. Zool. 75, 1553–1560 (1997).Article 

Google Scholar 
Madalozzo, B. Variação latitudinal nos limites de tolerância e plasticidade térmica em anfíbios em um cenário de mudanças climáticas: efeito dos micro-habitats, sazonalidade e filogenia. (Universidade Federal de Santa Maria, 2018).Mahoney, J. J. & Hutchison, V. H. Photoperiod acclimation and 24-hour variations in the critical thermal maxima of a tropical and a temperate frog. Oecologia 2, 143–161 (1969).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Maness, J. D. & Hutchison, V. H. Acute adjustment of thermal tolerance in vertebrate ectotherms following exposure to critical thermal maxima. J. Therm. Biol. 5, 225–233 (1980).Article 

Google Scholar 
Manis, M. L. & Claussen, D. L. Environmental and genetic influences on the thermal physiology of Rana sylvatica. J. Therm. Biol. 11, 31–36 (1986).Article 

Google Scholar 
Markle, T. M. & Kozak, K. H. Low acclimation capacity of narrow-ranging thermal specialists exposes susceptibility to global climate change. Ecol. Evol. 8, 4644–4656 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Marshall, E. & Grigg, G. C. Acclimation of CTM, LD50, and rapid loss of acclimation of thermal preferendum in tadpoles of Limnodynastes peronii (Anura, Myobatrachidae). Aust. Zool. 20, 447–456 (1980).
Google Scholar 
Mathias, J. H. The Comparative ecologies of two species of Amphibia (B. bufo and B. calamita) on the Ainsdale Sand Dunes National Nature Reserve. (The University of Manchester, 1971).McManus, J. J. & Nellis, D. W. The critical thermal maximum of the marine toad, Bufo marinus. Caribb. J. Sci. 15, 67–70 (1975).
Google Scholar 
Menke, M. E. & Claussen, D. L. Thermal acclimation and hardening in tadpoles of the bullfrog, Rana catesbeiana. J. Therm. Biol. 7, 215–219 (1982).Article 

Google Scholar 
Merino-Viteri, A. R. The vulnerability of microhylid frogs, Cophixalus spp., to climate change in the Australian Wet Tropics. (James Cook University, 2018).Messerman, A. F. Tales of an ‘invisible’ life stage: Survival and physiology among terrestrial juvenile ambystomatid salamanders. (University of Missouri, 2019).Meza-Parral, Y., García-Robledo, C., Pineda, E., Escobar, F. & Donnelly, M. A. Standardized ethograms and a device for assessing amphibian thermal responses in a warming world. J. Therm. Biol. 89 (2020).Miller, K. & Packard, G. C. Critical thermal maximum: Ecotypic variation between montane and piedmont chorus frogs (Pseudacris triseriata, Hylidae). Experientia 30, 355–356 (1974).CAS 
PubMed 
Article 

Google Scholar 
Miller, K. & Packard, G. C. An altitudinal cline in critical thermal maxima of chorus frogs (Pseudacris triseriata). Am. Nat. 111, 267–277 (1977).Article 

Google Scholar 
Mueller, C. A., Bucsky, J., Korito, L. & Manzanares, S. Immediate and persistent effects of temperature on oxygen consumption and thermal tolerance in embryos and larvae of the baja California chorus frog, Pseudacris hypochondriaca. Front. Physiol. 10 (2019).Navas, C. A., Antoniazzi, M. M., Carvalho, J. E., Suzuki, H. & Jared, C. Physiological basis for diurnal activity in dispersing juvenile Bufo granulosus in the Caatinga, a Brazilian semi-arid environment. Comp. Biochem. Physiol. 147, 647–657 (2007).Article 

Google Scholar 
Navas, C. A., Úbeda, C. A., Logares, R. & Jara, F. G. Thermal tolerances in tadpoles of three species of Patagonian anurans. S. Am. J. Herpetol. 5, 89–96 (2010).Article 

Google Scholar 
Nietfeldt, J. W., Jones, S. M., Droge, D. L. & Ballinger, R. E. Rate of thermal acclimation of larval Ambystoma tigrinum. J. Herpetol. 14, 209–211 (1980).Article 

Google Scholar 
Nol, R. & Ultsch, G. R. The roles of temperature and dissolved oxygen in microhabitat selection by the tadpoles of a frog (Rana pipiens) and a toad (Bufo terrestris). Copeia 1981, 645–652 (1981).Article 

Google Scholar 
Novarro, A. J. Thermal physiology in a widespread lungless salamander. (University of Maryland, 2018).Nowakowski, A. J. et al. Thermal biology mediates responses of amphibians and reptiles to habitat modification. Ecol. Lett. 21, 345–355 (2018).PubMed 
Article 

Google Scholar 
Orille, A. C., McWhinnie, R. B., Brady, S. P. & Raffel, T. R. Positive effects of acclimation temperature on the critical thermal maxima of Ambystoma mexicanum and Xenopus laevis. J. Herpetol. 54, 289–292 (2020).Article 

Google Scholar 
Oyamaguchi, H. M. et al. Thermal sensitivity of a neotropical amphibian (Engystomops pustulosus) and its vulnerability to climate change. Biotropica 50, 326–337 (2018).Article 

Google Scholar 
Paez Vacas, M. I. Mechanisms of population divergence along elevational gradients in the tropics. (Colorado State University, 2016).Paulson, B. K. & Hutchison, V. H. Blood changes in Bufo cognatus following acute heat stress. Comp. Biochem. Physiol. 87, 461–466 (1987).CAS 
Article 

Google Scholar 
Paulson, B. & Hutchison, V. Origin of the stimulus for muscular spasms at the critical thermal maximum in anurans. Copeia 810–813 (1987).Percino-Daniel, R. et al. Environmental heterogeneity shapes physiological traits in tropical direct-developing frogs. Ecol. Evol. (2021).Perotti, M. G., Bonino, M. F., Ferraro, D. & Cruz, F. B. How sensitive are temperate tadpoles to climate change? The use of thermal physiology and niche model tools to assess vulnerability. Zoology 127, 95–105 (2018).PubMed 
Article 

Google Scholar 
Pintanel, P., Tejedo, M., Almeida-Reinoso, F., Merino-Viteri, A. & Gutiérrez-Pesquera, L. M. Critical thermal limits do not vary between wild-caught and captive-bred tadpoles of Agalychnis spurrelli (Anura: Hylidae). Diversity 12, 43 (2020).Article 

Google Scholar 
Pintanel, P., Tejedo, M., Ron, S. R., Llorente, G. A. & Merino-Viteri, A. Elevational and microclimatic drivers of thermal tolerance in Andean Pristimantis frogs. J. Biogeogr. 46, 1664–1675 (2019).Article 

Google Scholar 
Pintanel, P. Thermal adaptation of amphibians in tropical mountains. Consequences of global warming. (Universitat de Barcelona, 2018).Pintanel, P., Tejedo, M., Salinas-Ivanenko, S., Jervis, P. & Merino-Viteri, A. Predators like it hot: Thermal mismatch in a predator-prey system across an elevational tropical gradient. J. Anim. Ecol. 90, 1985–1995 (2021).PubMed 
Article 

Google Scholar 
Pough, F. H. Natural daily temperature acclimation of eastern red efts, Notophthalmus v. viridescens (Rafinesque) (Amphibia: Caudata). Comp. Biochem. Physiol. 47, 71–78 (1974).CAS 
Article 

Google Scholar 
Pough, F. H., Stewart, M. M. & Thomas, R. G. Physiological basis of habitat partitioning in Jamaican. Eleutherodactylus. Oecologia 27, 285–293 (1977).ADS 
PubMed 
Article 

Google Scholar 
Quiroga, L. B., Sanabria, E. A., Fornés, M. W., Bustos, D. A. & Tejedo, M. Sublethal concentrations of chlorpyrifos induce changes in the thermal sensitivity and tolerance of anuran tadpoles in the toad Rhinella arenarum? Chemosphere 219, 671–677 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Rausch, C. The thermal ecology of the red-spotted toad, Bufo punctatus, across life history. (University of Nevada, 2007).Reichenbach, N. & Brophy, T. R. Natural history of the peaks of otter salamander (Plethodon hubrichti) along an elevational gradient. Herpetol. Bull. 141, 7–15 (2017).
Google Scholar 
Reider, K. E., Larson, D. J., Barnes, B. M. & Donnelly, M. A. Thermal adaptations to extreme freeze–thaw cycles in the high tropical Andes. Biotropica 53, 296–306 (2021).Article 

Google Scholar 
Richter-Boix, A. et al. Local divergence of thermal reaction norms among amphibian populations is affected by pond temperature variation. Evolution 69, 2210–2226 (2015).PubMed 
Article 

Google Scholar 
Riquelme, N. A., Díaz-Páez, H. & Ortiz, J. C. Thermal tolerance in the Andean toad Rhinella spinulosa (Anura: Bufonidae) at three sites located along a latitudinal gradient in Chile. J. Therm. Biol. 60, 237–245 (2016).PubMed 
Article 

Google Scholar 
Ritchart, J. P. & Hutchison, V. H. The effects of ATP and cAMP on the thermal tolerance of the mudpuppy. Necturus maculosus. J. Therm. Biol. 11, 47–51 (1986).CAS 
Article 

Google Scholar 
Rivera-Burgos, A. C. Habitat suitability for Eleutherodactylus frogs in Puerto Rico: Indexing occupancy, abundance and reproduction to climatic and habitat characteristics. (North Carolina State University, 2019).Rivera-Ordonez, J. M., Nowakowski, A. J., Manansala, A., Thompson, M. E. & Todd, B. D. Thermal niche variation among individuals of the poison frog, Oophaga pumilio, in forest and converted habitats. Biotropica 51, 747–756 (2019).Article 

Google Scholar 
Romero Barreto, P. Requerimientos fisiológicos y microambientales de dos especies de anfibios (Scinax ruber e Hyloxalus yasuni) del bosque tropical de Yasuní y sus implicaciones ante el cambio climático. (Pontificia Universidad Católica Del Ecuador, 2013).Ruiz-Aravena, M. et al. Impact of global warming at the range margins: Phenotypic plasticity and behavioral thermoregulation will buffer an endemic amphibian. Ecol. Evol. 4, 4467–4475 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Ruthsatz, K. et al. Thyroid hormone levels and temperature during development alter thermal tolerance and energetics of Xenopus laevis larvae. Conserv. Physiol. 6 (2018).Ruthsatz, K. et al. Post-metamorphic carry-over effects of altered thyroid hormone level and developmental temperature: physiological plasticity and body condition at two life stages in Rana temporaria. J. Comp. Physiol. B: Biochem. Syst. Environ. Physiol. 190, 297–315 (2020).CAS 
Article 

Google Scholar 
Rutledge, P. S., Spotila, J. R. & Easton, D. P. Heat hardening in response to two types of heat shock in the lungless salamanders Eurycea bislineata and Desmognathus ochrophaeus. J. Therm. Biol. 12, 235–241 (1987).Article 

Google Scholar 
Sanabria, E. et al. Effect of salinity on locomotor performance and thermal extremes of metamorphic Andean Toads (Rhinella spinulosa) from Monte Desert, Argentina. J. Therm. Biol. 74, 195–200 (2018).CAS 
PubMed 
Article 

Google Scholar 
Sanabria, E. A., González, E., Quiroga, L. B. & Tejedo, M. Vulnerability to warming in a desert amphibian tadpole community: the role of interpopulational variation. J. Zool. 313, 283–296 (2021).Article 

Google Scholar 
Sanabria, E. A. & Quiroga, L. B. Change in the thermal biology of tadpoles of Odontophrynus occidentalis from the Monte desert, Argentina: Responses to photoperiod. J. Therm. Biol. 36, 288–291 (2011).Article 

Google Scholar 
Sanabria, E. A., Quiroga, L. B., González, E., Moreno, D. & Cataldo, A. Thermal parameters and locomotor performance in juvenile of Pleurodema nebulosum (Anura: Leptodactylidae) from the Monte Desert. J. Therm. Biol. 38, 390–395 (2013).Article 

Google Scholar 
Sanabria, E. A., Quiroga, L. B. & Martino, A. L. Seasonal changes in the thermal tolerances of the toad Rhinella arenarum (Bufonidae) in the Monte Desert of Argentina. J. Therm. Biol. 37, 409–412 (2012).Article 

Google Scholar 
Sanabria, E. A., Quiroga, L. B. & Martino, A. L. Seasonal Changes in the thermal tolerances of Odontophrynus occidentalis (Berg, 1896) (Anura: Cycloramphidae). Belg. J. Zool. 143, 23–29 (2013).
Google Scholar 
Sanabria, E. A. et al. Thermal ecology of the post-metamorphic Andean toad (Rhinella spinulosa) at elevation in the monte desert, Argentina. J. Therm. Biol. 52, 52–57 (2015).PubMed 
Article 

Google Scholar 
Sanabria, E. A., Vaira, M., Quiroga, L. B., Akmentins, M. S. & Pereyra, L. C. Variation of thermal parameters in two different color morphs of a diurnal poison toad, Melanophryniscus rubriventris (Anura: Bufonidae). J. Therm. Biol. 41, 1–5 (2014).PubMed 
Article 

Google Scholar 
Sanabria, E. A. & Quiroga, L. B. Thermal parameters changes in males of Rhinella arenarum (Anura: Bufonidae) related to reproductive periods. Rev. Biol. Trop. 59, 347–353 (2011).PubMed 

Google Scholar 
Scheffers, B. R. et al. Thermal buffering of microhabitats is a critical factor mediating warming vulnerability of frogs in the Philippine biodiversity hotspot. Biotropica 45, 628–635 (2013).Article 

Google Scholar 
Scheffers, B. R., Edwards, D. P., Diesmos, A., Williams, S. E. & Evans, T. A. Microhabitats reduce animal’s exposure to climate extremes. Glob. Chang. Biol. 20, 495–503 (2014).ADS 
PubMed 
Article 

Google Scholar 
Schmid, W. D. High temperature tolerances of Bufo Hemiophrys and Bufo Cognatus. Ecology 46, 559–560 (1965).Article 

Google Scholar 
Sealander, J. A. & West, B. W. Critical thermal maxima of some Arkansas salamanders in relation to thermal acclimation. Herpetologica 25, 122–124 (1969).
Google Scholar 
Seibel, R. V. Variables affecting the critical thermal maximum of the leopard frog, Rana pipiens Schreber. Herpetologica 26, 208–213 (1970).
Google Scholar 
Sherman, E. Ontogenetic change in thermal tolerance of the toad Bufo woodhousii fowleri. Comp. Biochem. Physiol. 65, 227–230 (1980).ADS 
Article 

Google Scholar 
Sherman, E. Thermal biology of newts (Notophthalmus viridescens) chronically infected with a naturally occurring pathogen. J. Therm. Biol. 33, 27–31 (2008).Article 

Google Scholar 
Sherman, E., Baldwin, L., Fernandez, G. & Deurell, E. Fever and thermal tolerance in the toad Bufo marinus. J. Therm. Biol. 16, 297–301 (1991).Article 

Google Scholar 
Sherman, E. & Levitis, D. Heat hardening as a function of developmental stage in larval and juvenile Bufo americanus and Xenopus laevis. J. Therm. Biol. 28, 373–380 (2003).Article 

Google Scholar 
Shi, L., Zhao, L., Ma, X. & Ma, X. Selected body temperature and thermal tolerance of tadpoles of two frog species (Fejervarya limnocharis and Microhyla ornata) acclimated under different thermal conditions. Acta Ecol. Sin. 32, 0465–0471 (2012).Article 

Google Scholar 
Simon, M. N., Ribeiro, P. L. & Navas, C. A. Upper thermal tolerance plasticity in tropical amphibian species from contrasting habitats: Implications for warming impact prediction. J. Therm. Biol. 48, 36–44 (2015).PubMed 
Article 

Google Scholar 
Simon, M. Plasticidade fenotípica em relação à temperatura de larvas de Rhinella (Anura: Bufonidae) da caatinga e da floresta Atlântica. (Universidade de Sao Paulo, 2010).Skelly, D. K. & Freidenburg, L. K. Effects of beaver on the thermal biology of an amphibian. Ecol. Lett. 3, 483–486 (2000).Article 

Google Scholar 
Sos, T. Thermoconformity even in hot small temporary water bodies: a case study in yellow-bellied toad (Bombina v. variegata). Herpetol. Rom. 1, 1–11 (2007).
Google Scholar 
Spotila, J. R. Role of temperature and water in the ecology of lungless salamanders. Ecol. Monogr. 42, 95–125 (1972).Article 

Google Scholar 
Tracy, C. R., Christian, K. A., Betts, G. & Tracy, C. R. Body temperature and resistance to evaporative water loss in tropical Australian frogs. Comp. Biochem. Physiol. 150, 102–108 (2008).Article 

Google Scholar 
Turriago, J. L., Parra, C. A. & Bernal, M. H. Upper thermal tolerance in anuran embryos and tadpoles at constant and variable peak temperatures. Can. J. Zool. 93, 267–272 (2015).Article 

Google Scholar 
Vidal, M. A., Novoa-Muñoz, F., Werner, E., Torres, C. & Nova, R. Modeling warming predicts a physiological threshold for the extinction of the living fossil frog Calyptocephalella gayi. J. Therm. Biol. 69, 110–117 (2017).PubMed 
Article 

Google Scholar 
von May, R. et al. Divergence of thermal physiological traits in terrestrial breeding frogs along a tropical elevational gradient. Ecol. Evol. 7, 3257–3267 (2017).Article 

Google Scholar 
von May, R. et al. Thermal physiological traits in tropical lowland amphibians: Vulnerability to climate warming and cooling. PLoS ONE 14 (2019).Wagener, C., Kruger, N. & Measey, J. Progeny of Xenopus laevis from altitudinal extremes display adaptive physiological performance. J. Exp. Biol. 224 (2021).Wang, H. & Wang, L. Thermal adaptation of the common giant toad (Bufo gargarizans) at different earlier developmental stages. J. Agric. Univ. Hebei 31, 79–83 (2008).
Google Scholar 
Wang, L. The effects of constant and variable thermal acclimation on thermal tolerance of the common giant toad tadpoles (Bufo gargarizans). Acta Ecol. Sin. 34, 1030–1034 (2014).
Google Scholar 
Wang, L.-Z. & Li, X.-C. Effect of temperature on incubation and thermal tolerance of the Chinese forest frog. Chin. J. Zool. (2007).Wang, L. & Li, X.-C. Effects of constant thermal acclimation on thermal tolerance of the Chinese forest frog (Rana chensineniss). Acta Hydrobiol. Sin. 31, 748–750 (2007).CAS 

Google Scholar 
Wang, L.-Z., Li, X.-C. & Sun, T. Preferred temperature, avoidance temperature and lethal temperature of tadpoles of the common giant toad (Bufo gargarizans) and the Chinese forest frog (Rana chensinensis). Chin. J. Zool. 40, 23–27 (2005).
Google Scholar 
Warburg, M. R. On the water economy of Israel amphibians: The anurans. Comp. Biochem. Physiol. 40, 911–924 (1971).CAS 
Article 

Google Scholar 
Warburg, M. R. The water economy of Israel amphibians: The urodeles Triturus vittatus (Jenyns) and Salamandra salamandra (L.). Comp. Biochem. Physiol. 40, 1055–1056, IN11,1057–1063 (1971).Willhite, C. & Cupp, P. V. Daily rhythms of thermal tolerance in Rana clamitans (Anura: Ranidae) tadpoles. Comp. Biochem. Physiol. 72, 255–257 (1982).Article 

Google Scholar 
Wu, C.-S. & Kam, Y.-C. Thermal tolerance and thermoregulation by Taiwanese rhacophorid tadpoles (Buergeria japonica) living in geothermal hot springs and streams. Herpetologica 61, 35–46 (2005).Article 

Google Scholar 
Xu, X. The effect of temperature on body temperature and thermoregulation in different geographic populations of Rana dybowskii. (Harbin Normal University, 2017).Yandún Vela, M. C. Capacidad de aclimatación en renacuajos de dos especies de anuros: Rhinella marina (Bufonidae) y Gastrotheca riobambae (Hemiphractidae) y su vulnerabilidad al cambio climático. (Pontificia Universidad Católica Del Ecuador, 2017).Young, V. K. H. & Gifford, M. E. Limited capacity for acclimation of thermal physiology in a salamander. Desmognathus brimleyorum. J. Comp. Physiol. B: Biochem. Syst. Environ. Physiol. 183, 409–418 (2013).CAS 
Article 

Google Scholar 
Yu, Z., Dickstein, R., Magee, W. E. & Spotila, J. R. Heat shock response in the salamanders Plethodon jordani and Plethodon cinereus. J. Therm. Biol. 23, 259–265 (1998).CAS 
Article 

Google Scholar 
Zheng, R.-Q. & Liu, C.-T. Giant spiny-frog (Paa spinosa) from different populations differ in thermal preference but not in thermal tolerance. Aquat. Ecol. 44, 723–729 (2010).Article 

Google Scholar 
Zweifel, R. G. Studies on the critical thermal maxima of salamanders. Ecology 38, 64–69 (1957).Article 

Google Scholar 
Pick, J. L., Nakagawa, S. & Noble, D. W. A. Reproducible, flexible and high-throughput data extraction from primary literature: The metaDigitise r package. Methods Ecol. Evol. 10, 426–431 (2019).Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing.Jetz, W. & Pyron, R. A. The interplay of past diversification and evolutionary isolation with present imperilment across the amphibian tree of life. Nat. Ecol. Evol. 2, 850–858 (2018).PubMed 
Article 

Google Scholar 
AmphibiaWeb. https://amphibiaweb.org. University of California, Berkeley, California, USA (2022).Schwanz, L. E. et al. Best practices for building and curating databases for comparative analyses. J. Exp. Biol. 225, jeb243295 (2022).PubMed 
Article 

Google Scholar 
Pottier, P. et al. A comprehensive database of amphibian heat tolerance, Zenodo, https://doi.org/10.5281/zenodo.6565454 (2022).Lajeunesse, M. J. Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis. in Hanbook of Meta-analysis in Ecology and Evolution 195–206 (Princeton University Press, 2013).Nakagawa, S., et al. A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations. EcoEvoRxiv, https://doi.org/10.32942/osf.io/7thx9 (2022)Pottier, P., Burke, S., Drobniak, S. M., Lagisz, M. & Nakagawa, S. Sexual (in)equality? A meta-analysis of sex differences in thermal acclimation capacity across ectotherms. Funct. Ecol. 35, 2663–2678 (2021).Article 

Google Scholar 
Sunday, J. et al. Thermal tolerance patterns across latitude and elevation. Philos. Trans. R. Soc. B-Biol. Sci. 374, 20190036 (2019).Article 

Google Scholar 
Truebano, M., Fenner, P., Tills, O., Rundle, S. D. & Rezende, E. L. Thermal strategies vary with life history stage. J. Exp. Biol. 221, jeb171629 (2018).PubMed 
Article 

Google Scholar 
Rezende, E. L., Tejedo, M. & Santos, M. Estimating the adaptive potential of critical thermal limits: methodological problems and evolutionary implications. Funct. Ecol. 25, 111–121 (2011).Article 

Google Scholar 
Terblanche, J. S., Deere, J. A., Clusella-Trullas, S., Janion, C. & Chown, S. L. Critical thermal limits depend on methodological context. Proc. R. Soc. B-Biol. Sci. 274, 2935–2943 (2007).Article 

Google Scholar 
Hangartner, S., Sgrò, C. M., Connallon, T. & Booksmythe, I. Sexual dimorphism in phenotypic plasticity and persistence under environmental change: An extension of theory and meta-analysis of current data. Ecol. Lett. (2022).Wickham, H. et al. Welcome to the tidyverse. J. Open Source Softw. 4, 1686 (2019).ADS 
Article 

Google Scholar 
Dunnington, D. & Thorne, B. ggspatial: Spatial Data Framework for ggplot2. R package (2020).Brownrigg, M. R. Package ‘maps’. R package (2013).Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T.-Y. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol. 8, 28–36 (2017).Article 

Google Scholar 
Xu, S. et al. ggtreeExtra: Compact visualization of richly annotated phylogenetic data. Mol. Biol. Evol. 38, 4039–4042 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Campitelli, E. ggnewscale: Multiple fill and colour scales in “ggplot2”. R package (2020).Pedersen, T. L. patchwork: The Composer of Plots. R package (2020).Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).CAS 
PubMed 
Article 

Google Scholar  More

.readcube-buybox { display: none !important;}
An endangered lemur species that lives in Madagascar’s rainforest could vanish within 25 years if deforestation on the island isn’t reduced1.

Access options

/* style specs start */
style{display:none!important}.LiveAreaSection-193358632 *{align-content:stretch;align-items:stretch;align-self:auto;animation-delay:0s;animation-direction:normal;animation-duration:0s;animation-fill-mode:none;animation-iteration-count:1;animation-name:none;animation-play-state:running;animation-timing-function:ease;azimuth:center;backface-visibility:visible;background-attachment:scroll;background-blend-mode:normal;background-clip:borderBox;background-color:transparent;background-image:none;background-origin:paddingBox;background-position:0 0;background-repeat:repeat;background-size:auto auto;block-size:auto;border-block-end-color:currentcolor;border-block-end-style:none;border-block-end-width:medium;border-block-start-color:currentcolor;border-block-start-style:none;border-block-start-width:medium;border-bottom-color:currentcolor;border-bottom-left-radius:0;border-bottom-right-radius:0;border-bottom-style:none;border-bottom-width:medium;border-collapse:separate;border-image-outset:0s;border-image-repeat:stretch;border-image-slice:100%;border-image-source:none;border-image-width:1;border-inline-end-color:currentcolor;border-inline-end-style:none;border-inline-end-width:medium;border-inline-start-color:currentcolor;border-inline-start-style:none;border-inline-start-width:medium;border-left-color:currentcolor;border-left-style:none;border-left-width:medium;border-right-color:currentcolor;border-right-style:none;border-right-width:medium;border-spacing:0;border-top-color:currentcolor;border-top-left-radius:0;border-top-right-radius:0;border-top-style:none;border-top-width:medium;bottom:auto;box-decoration-break:slice;box-shadow:none;box-sizing:border-box;break-after:auto;break-before:auto;break-inside:auto;caption-side:top;caret-color:auto;clear:none;clip:auto;clip-path:none;color:initial;column-count:auto;column-fill:balance;column-gap:normal;column-rule-color:currentcolor;column-rule-style:none;column-rule-width:medium;column-span:none;column-width:auto;content:normal;counter-increment:none;counter-reset:none;cursor:auto;display:inline;empty-cells:show;filter:none;flex-basis:auto;flex-direction:row;flex-grow:0;flex-shrink:1;flex-wrap:nowrap;float:none;font-family:initial;font-feature-settings:normal;font-kerning:auto;font-language-override:normal;font-size:medium;font-size-adjust:none;font-stretch:normal;font-style:normal;font-synthesis:weight style;font-variant:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;grid-auto-columns:auto;grid-auto-flow:row;grid-auto-rows:auto;grid-column-end:auto;grid-column-gap:0;grid-column-start:auto;grid-row-end:auto;grid-row-gap:0;grid-row-start:auto;grid-template-areas:none;grid-template-columns:none;grid-template-rows:none;height:auto;hyphens:manual;image-orientation:0deg;image-rendering:auto;image-resolution:1dppx;ime-mode:auto;inline-size:auto;isolation:auto;justify-content:flexStart;left:auto;letter-spacing:normal;line-break:auto;line-height:normal;list-style-image:none;list-style-position:outside;list-style-type:disc;margin-block-end:0;margin-block-start:0;margin-bottom:0;margin-inline-end:0;margin-inline-start:0;margin-left:0;margin-right:0;margin-top:0;mask-clip:borderBox;mask-composite:add;mask-image:none;mask-mode:matchSource;mask-origin:borderBox;mask-position:0 0;mask-repeat:repeat;mask-size:auto;mask-type:luminance;max-height:none;max-width:none;min-block-size:0;min-height:0;min-inline-size:0;min-width:0;mix-blend-mode:normal;object-fit:fill;object-position:50% 50%;offset-block-end:auto;offset-block-start:auto;offset-inline-end:auto;offset-inline-start:auto;opacity:1;order:0;orphans:2;outline-color:initial;outline-offset:0;outline-style:none;outline-width:medium;overflow:visible;overflow-wrap:normal;overflow-x:visible;overflow-y:visible;padding-block-end:0;padding-block-start:0;padding-bottom:0;padding-inline-end:0;padding-inline-start:0;padding-left:0;padding-right:0;padding-top:0;page-break-after:auto;page-break-before:auto;page-break-inside:auto;perspective:none;perspective-origin:50% 50%;pointer-events:auto;position:static;quotes:initial;resize:none;right:auto;ruby-align:spaceAround;ruby-merge:separate;ruby-position:over;scroll-behavior:auto;scroll-snap-coordinate:none;scroll-snap-destination:0 0;scroll-snap-points-x:none;scroll-snap-points-y:none;scroll-snap-type:none;shape-image-threshold:0;shape-margin:0;shape-outside:none;tab-size:8;table-layout:auto;text-align:initial;text-align-last:auto;text-combine-upright:none;text-decoration-color:currentcolor;text-decoration-line:none;text-decoration-style:solid;text-emphasis-color:currentcolor;text-emphasis-position:over right;text-emphasis-style:none;text-indent:0;text-justify:auto;text-orientation:mixed;text-overflow:clip;text-rendering:auto;text-shadow:none;text-transform:none;text-underline-position:auto;top:auto;touch-action:auto;transform:none;transform-box:borderBox;transform-origin:50% 50%0;transform-style:flat;transition-delay:0s;transition-duration:0s;transition-property:all;transition-timing-function:ease;vertical-align:baseline;visibility:visible;white-space:normal;widows:2;width:auto;will-change:auto;word-break:normal;word-spacing:normal;word-wrap:normal;writing-mode:horizontalTb;z-index:auto;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;margin:0}.LiveAreaSection-193358632{width:100%}.LiveAreaSection-193358632 .login-option-buybox{display:block;width:100%;font-size:17px;line-height:30px;color:#222;padding-top:30px;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-access-options{display:block;font-weight:700;font-size:17px;line-height:30px;color:#222;font-family:Harding,Palatino,serif}.LiveAreaSection-193358632 .additional-login >li:not(:first-child)::before{transform:translateY(-50%);content:””;height:1rem;position:absolute;top:50%;left:0;border-left:2px solid #999}.LiveAreaSection-193358632 .additional-login >li:not(:first-child){padding-left:10px}.LiveAreaSection-193358632 .additional-login >li{display:inline-block;position:relative;vertical-align:middle;padding-right:10px}.BuyBoxSection-683559780{display:flex;flex-wrap:wrap;flex:1;flex-direction:row-reverse;margin:-30px -15px 0}.BuyBoxSection-683559780 .box-inner{width:100%;height:100%}.BuyBoxSection-683559780 .readcube-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:1;flex-basis:255px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:300px;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .subscribe-buybox-nature-plus{background-color:#f3f3f3;flex-shrink:1;flex-grow:4;flex-basis:100%;background-clip:content-box;padding:0 15px;margin-top:30px}.BuyBoxSection-683559780 .title-readcube{display:block;margin:0;margin-right:20%;margin-left:20%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-buybox{display:block;margin:0;margin-right:29%;margin-left:29%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .title-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:24px;line-height:32px;color:#222;padding-top:30px;text-align:center;font-family:Harding,Palatino,serif}.BuyBoxSection-683559780 .asia-link{color:#069;cursor:pointer;text-decoration:none;font-size:1.05em;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:1.05em6}.BuyBoxSection-683559780 .access-readcube{display:block;margin:0;margin-right:10%;margin-left:10%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-asia-buybox{display:block;margin:0;margin-right:5%;margin-left:5%;font-size:14px;color:#222;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .access-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;padding-top:10px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .usps-buybox{display:block;margin:0;margin-right:30%;margin-left:30%;font-size:14px;color:#222;opacity:.8px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .price-buybox{display:block;font-size:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;padding-top:30px;text-align:center}.BuyBoxSection-683559780 .price-from{font-size:14px;padding-right:10px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:20px}.BuyBoxSection-683559780 .issue-buybox{display:block;font-size:13px;text-align:center;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:19px}.BuyBoxSection-683559780 .no-price-buybox{display:block;font-size:13px;line-height:18px;text-align:center;padding-right:10%;padding-left:10%;padding-bottom:20px;padding-top:30px;color:#222;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif}.BuyBoxSection-683559780 .vat-buybox{display:block;margin-top:5px;margin-right:20%;margin-left:20%;font-size:11px;color:#222;padding-top:10px;padding-bottom:15px;text-align:center;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;line-height:17px}.BuyBoxSection-683559780 .button-container{display:flex;padding-right:20px;padding-left:20px;justify-content:center}.BuyBoxSection-683559780 .button-container >*{flex:1px}.BuyBoxSection-683559780 .button-container >a:hover,.Button-505204839:hover,.Button-1078489254:hover,.Button-2808614501:hover{text-decoration:none}.BuyBoxSection-683559780 .readcube-button{background:#fff;margin-top:30px}.BuyBoxSection-683559780 .button-asia{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;margin-top:75px}.BuyBoxSection-683559780 .button-label-asia,.ButtonLabel-3869432492,.ButtonLabel-3296148077,.ButtonLabel-1566022830{display:block;color:#fff;font-size:17px;line-height:20px;font-family:-apple-system,BlinkMacSystemFont,”Segoe UI”,Roboto,Oxygen-Sans,Ubuntu,Cantarell,”Helvetica Neue”,sans-serif;text-align:center;text-decoration:none;cursor:pointer}.Button-505204839,.Button-1078489254,.Button-2808614501{background:#069;border:1px solid #069;border-radius:0;cursor:pointer;display:block;padding:9px;outline:0;text-align:center;text-decoration:none;min-width:80px;max-width:320px;margin-top:10px}.Button-505204839 .readcube-label,.Button-1078489254 .readcube-label,.Button-2808614501 .readcube-label{color:#069}
/* style specs end */Subscribe to Nature+Get immediate online access to the entire Nature family of 50+ journals$29.99monthlySubscribe to JournalGet full journal access for 1 year$199.00only $3.90 per issueAll prices are NET prices.VAT will be added later in the checkout.Tax calculation will be finalised during checkout.Buy articleGet time limited or full article access on ReadCube.$32.00All prices are NET prices.

Additional access options:

doi: https://doi.org/10.1038/d41586-022-03116-6

References

Subjects

Conservation biology More

Study areaWe conducted our study in two suburbs in Wellington, New Zealand (Fig. 1). The 4.7-hectare site in the suburb of Kelburn (-41.285°S, 174.770°E) was situated on the grounds of student accommodation for Victoria University of Wellington. The site comprised bungalow houses, two accommodation halls, and access roads and paths. About half of the vegetation at the Kelburn site was a mix of tended grass lawns and gardens containing a variety of native New Zealand plant species, e.g., flax (Phormium spp.), longwood tussock (Carex comans), and cabbage tree (Cordyline australis). The other half was a mix of dense ground cover dominated by invasive weed species and native and exotic trees and shrubs, e.g., pōhutukawa (Metrosideros excelsa), common oak (Quercus robur), kawakawa (Piper excelsum), and taupata (Coprosma repens). The second suburb was Roseneath (−41.292°S, 174.801°E) on a small peninsula on the north-eastern side of Mount Victoria. The site was 8.5 hectares comprising 76 residential properties, public thoroughfares, and footpaths. We conducted fieldwork in the gardens of 25 of these properties. The vegetation varied considerably between gardens, comprising native and introduced garden plants and invasive weeds, especially blackberry (Rubus fruticosus).Figure 1(A) The study was conducted in the suburbs of Kelburn (left yellow dot) and Roseneath (right yellow dot) in the city of Wellington, New Zealand. The black polygon represents the 1475 ha area that will be targeted for ship rat (Rattus rattus) eradication in Wellington city, New Zealand. In each suburb, we radio-collared ship rats and deployed three types of devices (bait stations, chew cards, and WaxTags) to estimate home range and detection parameters. (B) In Kelburn, we radio-collared 14 rats and deployed eight devices. (C) In Roseneath, we radio-collared 16 rats and deployed 30 devices. The yellow circles indicate home range centers of individual rats, the red triangles indicate the location of bait stations and detection devices, and the small black dots indicate the telemetry locations of rats.Full size imageRat capture, radio-collaring, and field methodologyWe set 100 live-capture cage traps (custom-made, spring-loaded traps) in Kelburn from 12 July to 15 August 2020, and another 100 in Roseneath from 20 August to 20 October 2020. We baited cage traps with apple coated in chocolate spread and checked them at least once every 24 h. We set cage traps in areas with complex vegetative groundcover and understorey to maximize capture rates of ship rats (see35), and to provide shelter from inclement weather. We provided additional shelter by inserting bedding inside a tin can placed in the cage traps, along with a plastic cover over the traps to limit exposure to wind and rain. Cage traps were active for 5 days per week on average. We released all non-target species (house mice Mus musculus, European hedgehogs Erinaceus europaeus, and Eurasian blackbirds Turdus merula).We transferred any trap containing a captured rat into a sealed plastic container. Depending on the estimated size of the captured rat, we placed between one and three cotton balls soaked in isoflurane (99.9%, Attane, Piramal Critical Care Inc., Bethlehem, Pennsylvania, USA) inside the plastic container. A rat was anesthetized when it lost balance and was unable to regain balance when we gently rotated the container. We then removed the rat from the cage trap and placed it next to a heat pad with its head close to the cotton balls soaked in isoflurane to maintain anaesthesia while handling them. We fitted all rats weighing  > 110 g with a V1C 118B VHF radio-collar (Lotek, Havelock North, New Zealand). We marked each collared rat with a unique pelage code using a permanent blonde hair dye60. We also recorded biometrics, including sex, weight, and length. When processing was finished, we placed the rat into another container to recover. This container had a heating pad for warmth and an apple for food to avoid a drop in body temperature and hypoglycemia, which are common problems with anaesthesia62. When the rat appeared mobile, energetic, and behaving normally, we released it at the point of capture.We monitored radio-collared rats using a Yagi antenna (Lotek, Havelock North, New Zealand) and a Telonics R-1000 receiver (Telonics Inc., Mesa, Arizona, USA). We conducted radio-telemetry work during August–November 2020, with fixes taken during the day and night. We recorded a total of three fixes per rat per night, taken at two-hour intervals between the hours of sunset (2200 h) and sunrise (0500 h). We mostly attempted one day-time fix (1200 h); however, if a tracked rat was active (determined by a VHF signal that was moving or changing amplitude), we attempted a second fix in the afternoon. To minimize location error, we used the close approach radio-tracking method described by63. Once a successful fix was made, we used a handheld GPS unit to record the location, date, and time. Telemetry fixes were collected for each radio-collared rat for 18–97 days.After approximately one week of radiotracking an animal, we obtained an initial crude estimate of the center of each rat’s home range as the mean of all eastings and northings (based on a minimum of 15 telemetry points per rat). A bait station baited with non-toxic pellets (Protecta Sidekick bait stations, Bell Laboratories Inc., Windsor, Wisconsin, USA), a WaxTag with a peanut butter odor incorporated into the wax (PCR WaxTags, Traps.co.nz, Rolleston, New Zealand), and a chew card (a corflute card baited with peanut butter) were deployed at varying distances (max. 50 m) and cardinal directions from the estimated home range center of each individual rat. This layout maximized the likelihood of encounters with devices, compared with a regular grid-type deployment where some of the devices could fall outside a collared rat’s home range and thus never be encountered. Note that the crude estimate of the location of the home range center for each rat was only used to guide device placement, i.e., it was not used in any statistical analyses, or to describe rat home range sizes. Further, to avoid a choice-type experiment (i.e., all three devices set immediately next to each other), we randomly assigned a distance and cardinal direction to each device type within each rat’s home range but ensured all devices were deployed  > 15 m apart. The three device types were chosen because they are used by Predator Free Wellington to conduct their eradication operations.Every deployed device had a trail camera (Browning Strike Force HD Pro Micro Series, Morgan, Utah, USA) taking video of rats encountering and interacting with the device. We set cameras to take 20 s of video footage when triggered, followed by a 1 s re-trigger interval. We fixed trail cameras to trees at a height of 50 cm above ground level and placed the devices 1.5 m in front of the camera (after64). This strategy allowed accurate identification of pelage codes on marked rats. We cleared vegetation in front of and immediately behind the trail cameras to avoid accidental triggers. We used pegs to mark a 30-cm-radius circle around each device and considered a rat–device encounter when a rat entered that circle. We serviced trail camera–device pairs at least once every three days. This included adding more non-lethal bait to bait stations and peanut butter to monitoring devices, installing new WaxTags or chew cards if they had been destroyed, and replacing batteries and SD cards in trail cameras. We set up 54 trail camera–device pairs. However, due to trail camera malfunctions, we were able to retrieve footage from only 38 cameras, 8 in Kelburn and 30 in Roseneath. Trail camera–device pairs were active for 20–70 days, but we retained data from only the first 20 days for the analyses.Video processingAll video footage was viewed and interpreted by the same individual (HRM) for consistency. We extracted the following information: date and time of rat sightings, rat ID (according to the pelage code, or designated as ‘R’ for unmarked rats), the duration of the visit to a device, whether or not an encounter occurred (as defined above), and whether or not an interaction occurred. We defined an interaction as a rat either gnawing on a chew card or WaxTag or entering a bait station.Data analysisWe combined all ship rat telemetry data with the device encounter and interaction data, and developed a hierarchical Bayesian model to infer factors influencing the key parameters σ, ε0, and θ. The analytical approach builds on that described in65. For the purpose of estimating ε0 and θ, multiple encounters or interactions by the same individual with the same device on the same night were counted as a single encounter or interaction.The VHF telemetry data Zij were composed of xij (eastings) and yij (northings) locations for each individual rat i at site j (either Kelburn or Roseneath). To simplify the notation, we drop the j subscript from all subsequent equations. We modelled the probability of observing Zi as a symmetric bivariate normal variable$$P({Z}_{i})= prod_{i=1}^{{L}_{i}}Normal(Delta {x}_{i}|0,{sigma }_{i}^{2})Normal(Delta {y}_{i}|0,{sigma }_{i}^{2})$$
(1)
where σi is the standard deviation of a normal distribution with zero mean, Li is the number of location fixes for individual i, and Δxi and Δyi are the straight-line distances from the home range center of individual i to xi and yi, respectively.Home range centers can be estimated using various methods, all of which have underlying assumptions (e.g.,66,67). We calculated the home range center for each individual as the mean of all xi and yi, i.e., the centroid of all locations that we recorded for each individual ( > 30 VHF fixes in all instances). Under this formulation, the home range center is assumed to be perfectly observed, an assumption that is supported by the sample size of telemetry locations that we obtained for each individual (see Supplementary Table 266).We modelled σi as a log-normal variable with mean ln(μi), which was a function of the sex of the individual:$$lnleft({sigma }_{i}right)sim Normal(mathit{ln}left({mu }_{i}right), V)$$
(2)
$$lnleft({mu }_{i}right)= {beta }_{0}+ {beta }_{1}{sex}_{i}$$
(3)
where V is the variance of ln(σi), and ln(μi) is a linear function of a categorical variable indicating whether rat i is a male (0) or a female (1). The priors on the β coefficients and V were Normal(0, 10) and InverseGamma(0.01, 0.01), respectively.The encounter data (Eimt) across all devices m and nights t was modelled as a Bernoulli process:$${E}_{imt}sim Bernoulli({gamma }_{imt})$$
(4)
$$logitleft({gamma }_{imt}right)sim MultivariateNormal(logitleft({P}_{imt}right), varSigma )$$
(5)
where γimt is a latent variable representing the degree to which the nightly probability of rat i encountering a given device is not independent of the encounter outcomes of nearby devices, i.e., we assumed there is spatial autocorrelation in the nightly probability of encountering a device. To account for the spatial autocorrelation not explained by the covariates explicitly modelled (i.e., σ and device type, see below), we included an exponential spatial covariance error structure (Σ) as follows:$$varSigma = {nu }^{2}{e}^{-varphi r}$$
(6)
where ν2 is the variance, φ is a correlation distance parameter, and r is the distance (in m) between pairs of devices68,69. Further, because not all devices were available on all nights, Σ was calculated iteratively for each night considering only those devices that were available. We used moderately informative log-normal priors for the covariance parameters to obtain proper posteriors69: ν2 ~ logN(3,1) and φ ~ logN(1,1).The nightly probability of encounter of device m by individual i on night t (Pimt) was calculated using a half-normal detection function70:$${P}_{imt}= {{left({varepsilon }_{0, im}{e}^{left(-frac{{d}_{im}^{2}}{2{sigma }_{i}^{2}}right)}right)}^{{tau E}_{it}^{*}}}times {{left({varepsilon }_{0,im}{e}^{left(-frac{{d}_{im}^{2}}{2{sigma }_{i}^{2}}right)}right)}^{1-{E}_{it}^{*}}}$$
(7)
where ε0,im is the maximum nightly probability of encounter for device m, or the probability if device m was placed at the center of the home range of rat i. The variable σi is the standard deviation from Eq. (1) (i.e., σi is estimated jointly from the telemetry and encounter data) and dim is the distance (in m) between the home range center of rat i and device m; only devices within a distance of 3.72σi from the home range center were considered in the calculation in Eq. (7)70. Finally, τ is a strictly positive parameter (i.e., τ  > 0), measuring the degree of device-shyness, which is multiplied by an indicator variable (left({E}_{it}^{*}right)) which takes a value of 0 when individual i has not encountered a device (of any type) on nights prior to night t, or a value of 1 if it had previously encountered one, regardless of the type of device it encountered. If τ  1 then rats are ‘device-shy’ and thus more likely to avoid devices on nights following an initial encounter. ({E}_{it}^{*}) was reset to 0 after 20 days of no encounters with a device. Following65 we set the prior on τ as Gamma(0.933, 8.33) (shape and rate parameters, respectively).Values of ε0,im were predicted as a function of σi, device type, and individual effects using the following equation:$$logitleft({varepsilon }_{0, im}right)={alpha }_{0}+ {alpha }_{1}mathrm{ln}left({sigma }_{i}right)+ {alpha }_{2}{chewcard}_{m}+{alpha }_{3}{waxtag}_{m}+{delta }_{i}$$
(8)
where α2 and α3 quantify the increase or decrease in the maximal probability of encountering a chew card or a WaxTag relative to a bait station (which is the reference category). The δi parameters account for individual differences in ε0. Finally, we allowed ε0 to be a function of ln(σi) because we assumed encounter probability at home range center will decrease with increasing home range size (as suggested by71 and shown by65). The priors on the α coefficients and δ were Normal(0, 10) and Normal(0, 1), respectively.The interaction data (Iimn) across all devices m and nights n when encounters occurred was modelled as a Bernoulli process with probability θ, which was a function of device type and individual effects:$${mathrm{I}}_{imn}sim Bernoullileft({theta }_{imn}right)$$
(9)
$$logitleft({theta }_{imn}right)={lambda }_{0}+ {lambda }_{1}{chewcard}_{m}+{lambda }_{2}{waxtag}_{m}+{lambda }_{3}{I}_{in}^{*}+{rho }_{i}$$
(10)
where θimn is the probability of rat i interacting with device m given that it has encountered it on night n, and λ1 and λ2 quantify the increase or decrease in the conditional probability of interaction for a chew card or a WaxTag relative to a bait station. The λ3 parameter is analogous to τ in Eq. (7) but for the process of interaction given encounter with a device. However, by incorporating λ3 directly into a linear equation, this parameter can take negative values and thus should be interpreted differently to τ: if λ3  0 indicates that individuals become ‘device-happy’ after an initial interaction. This parameter is multiplied by an indicator variable ({(I}_{in}^{*})) which takes a value of 0 when individual i has not interacted with a device (of any type) on nights prior to night n, or a value of 1 when it has interacted with one previously, regardless of the type of device it interacted with. If a rat had not interacted with a device for 20 days, ({I}_{in}^{*}) was reset to 0. Finally, the ρi parameters account for individual differences in θ. The priors on the λ coefficients and ρ were Normal(0, 10) and Normal(0, 1), respectively. Although we explicitly modelled spatial autocorrelation in the probability of encountering a device, we did not do so for the probability of interaction given an encounter. In this instance we assumed that whether an animal chose to interact with an encountered device would depend on its previous experience (as quantified by λ3) rather than the spatial location of nearby devices.We used Markov Chain Monte Carlo (MCMC) simulation to estimate model parameters using Python programming language. The variance parameter V was sampled from the full conditional posteriors, but all other parameters were estimated using the Metropolis algorithm69. Posterior summaries were taken from four chains containing 3000 samples each (with a burn-in of 2000 and a thinning rate of 30). Convergence on posteriors was assessed by visual inspection and a scale reduction factor  More

Neo, M. L., Eckman, W., Vicentuan, K., Teo, S.L.-M. & Todd, P. A. The ecological significance of giant clams in coral reef ecosystems. Biol. Conserv. 181, 111–123 (2015).Article 

Google Scholar 
Wolfe, K. et al. Priority species to support the functional integrity of coral reefs. Oceanogr. Mar. Biol. Annu. Rev. 58, 179–318 (2020).Article 

Google Scholar 
Ip, Y. K. & Chew, S. F. Light-dependent phenomena and related molecular mechanisms in giant clam-dinoflagellate associations: A review. Front. Mar. Sci. 8, 627722 (2021).Article 

Google Scholar 
Rossbach, S. et al. Flexibility in Red Sea Tridacna maxima-symbiodiniaceae associations supports environmental niche adaption. Ecol. Evol. 11, 3393–3406 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Neo, M. L. et al. Giant clams (Bivalvia: Cardiidae: Tridacninae): A comprehensive update of species and their distribution, current threats and conservation status. Oceanogr. Mar. Biol. Annu. Rev. 55, 87–388 (2017).Article 

Google Scholar 
Armstrong, E. J., Dubousquet, V., Mills, S. C. & Stillman, J. H. Elevated temperature, but not acidification, reduces fertilization success in the small giant clam, Tridacna maxima. Mar. Biol. 167, 8 (2020).CAS 
Article 

Google Scholar 
Lokier, S., Al-Suwaidi, A. E. & Steuber, T. Stable isotope sclerochronology of Pleistocene shells of the ‘Giant Clam’ Tridacna from Abu Dhabi. Tribulus 20, 21–23 (2012).
Google Scholar 
Obura, D. The diversity and biogeography of Western Indian Ocean reef-building corals. PLoS ONE 7, e45013 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kulbicki, M. et al. Biogeography of butterflyfishes: A global model for reef fishes? In Biology of Butterflyfishes (eds Pratchett, M. S. et al.) 70–106 (CRC Press, 2013).Chapter 

Google Scholar 
DiBattista, J. D. et al. On the origin of endemic species in the Red Sea. J. Biogeogr. 43, 13–30 (2016).Article 

Google Scholar 
Kemp, J. M. Zoogeography of the coral reef fishes of the north-eastern Gulf of Aden, with eight new records of coral reef fishes from Arabia. Fauna Arabia 18, 293–321 (2000).
Google Scholar 
Sheppard, C. R. C. & Salm, R. V. Reef and coral communities of Oman, with a description of a new coral species (Order Scleractinia, genus Acanthastrea). J. Nat. Hist. 22, 263–279 (1988).Article 

Google Scholar 
Burt, J. A. et al. Biogeographic patterns of reef fish community structure in the northeastern Arabian Peninsula. ICES J. Mar. Sci. 68, 1875–1883 (2011).Article 

Google Scholar 
Torquato, F. & Møller, P. R. Physical-biological interactions underlying the connectivity patterns of coral-dependent fishes around the Arabian Peninsula. J. Biogeogr. 49, 483–496 (2022).Article 

Google Scholar 
Watanabe, T., Suzuki, A., Kawahata, H., Kan, H. & Ogawa, S. A 60-year isotopic record from a mid-Holocene fossil giant clam (Tridacna gigas) in the Ryukyu Islands: Physiological and paleoclimatic implications. Palaeogeogr. Palaeoclimatol. Palaeoecol. 212, 343–354 (2004).Article 

Google Scholar 
Elliot, M. et al. Profiles of trace elements and stable isotopes derived from giant long-lived Tridacna gigas bivalves: Potential applications in paleoclimatic studies. Palaeogeogr. Palaeoclimatol. Palaeoecol. 280, 123–142 (2009).Article 

Google Scholar 
Welsh, K., Elliot, M., Tudhope, A., Ayling, B. & Chappell, J. Giant bivalves (Tridacna gigas) as recorders of ENSO variability. Earth Planet. Sci. Lett. 307, 266–270 (2011).ADS 
CAS 
Article 

Google Scholar 
Hori, M. et al. Middle Holocene daily light cycle reconstructed from the strontium/calcium ratios of a fossil giant clam shell. Sci. Rep. 5, 8734 (2015).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Komagoe, T., Watanabe, T., Shirai, K., Yamazaki, A. & Uematu, M. Geochemical and microstructural signals in giant clam Tridacna maxima recorded typhoon events at Okinotori Island, Japan. J. Geophys. Res. Biogeosci. 123, 1460–1474 (2018).CAS 
Article 

Google Scholar 
Yuan, Y., Kusky, T. M. & Rajendran, S. Tertiary and Quaternary marine terraces and planation surfaces of northern Oman: Interaction of flexural bulge migration associated with the Arabian-Eurasian collision and eustatic sea level changes. J. Earth Sci. 27, 955–970 (2016).CAS 
Article 

Google Scholar 
Louis, V., Besseau, L. & Lartaud, F. Step in time: Biomineralisation of bivalve’s shell. Front. Mar. Sci. 9, 906085 (2022).Article 

Google Scholar 
Mossadegh, Z. K. et al. Palaeoecology of well-preserved coral communities in a siliciclastic environment from the Late Pleistocene (MIS 7), Kish Island, Persian Gulf (Iran): The development of low-relief reef frameworks (biostromes) in increasingly restricted environments. Int. J. Earth Sci. 102, 545–570 (2013).Article 

Google Scholar 
Pico, T., Creveling, J. R. & Mitrovica, J. X. Sea-level records from the U.S. mid-Atlantic constrain laurentide ice sheet extent during marine isotope stage 3. Nat. Commun. 8, 15612 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hoffmann, G. et al. Quaternary uplift along a passive continental margin (Oman, Indian Ocean). Geomorphology 350, 106870 (2020).Article 

Google Scholar 
Grant, K. M. et al. Rapid coupling between ice volume and polar temperature over the past 150,000 years. Nature 491, 744–747 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Lambeck, K., Rouby, H., Purcell, A., Sun, Y. & Sambridge, M. Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proc. Natl. Acad. Sci. 111, 15296–15303 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kiessling, W., Simpson, C., Beck, B., Mewis, H. & Pandolfi, J. M. Equatorial decline of reef corals during the last Pleistocene interglacial. Proc. Natl. Acad. Sci. 109, 21378–21383 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Burns, S. J., Matter, A., Frank, N. & Mangini, A. Speleothem-based paleoclimate record from northern Oman. Geology 26, 499–502 (1998).ADS 
Article 

Google Scholar 
Hoffmann, G., Rupprechter, M., Rahn, M. & Preusser, F. Fluvio-lacustrine deposits reveal precipitation pattern in SE Arabia during early MIS 3. Quat. Int. 382, 145–153 (2015).Article 

Google Scholar 
Kobashi, T. & Grossman, E. J. The oxygen isotopic record of seasonality in Conus shells and its application to understanding late middle Eocene (38 Ma) climate. Paleontol. Res. 7, 343–355 (2003).Article 

Google Scholar 
Watanabe, T. K. et al. Past summer upwelling events in the Gulf of Oman derived from a coral geochemical record. Sci. Rep. 7, 4568 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jayaram, C. et al. Analysis of gap-free chlorophyll-α data from MODIS in Arabian Sea, reconstructed using DINEOF. Int. J. Remote Sens. 39, 7506–7522 (2018).Article 

Google Scholar 
Warter, V., Erez, J. & Müller, J. Environmental and physiological controls on daily trace element incorporation in Tridacna crocea from combined laboratory culturing and ultra-high resolution LA-ICP-MS analysis. Palaeogeogr. Palaeoclimatol. Palaeoecol. 496, 32–47 (2018).Article 

Google Scholar 
Ayouche, A. et al. Structure and dynamics of the Ras al Hadd oceanic dipole in the Arabian Sea. Oceans 2, 105–125 (2021).Article 

Google Scholar 
Sano, Y. et al. Past daily light cycle recorded in the strontium/calcium ratios of giant clam shells. Nat. Commun. 3, 761 (2012).ADS 
PubMed 
Article 

Google Scholar 
Santos, G. M. et al. Δ14C and δ13C of seawater DIC as tracers of coastal upwelling: A 5-year time series from Southern California. Radiocarbon 53, 669–677 (2011).CAS 
Article 

Google Scholar 
North Greenland Ice Core Project Members. High-resolution record of Northern Hemisphere climate extending into the last interglacial period. Nature 431, 147–151 (2004).Article 

Google Scholar 
Zhang, X. & Prange, M. Stability of the Atlantic overturning circulation under intermediate (MIS3) and full glacial (LGM) conditions and its relationship with Dansgaard-Oeschger climate variability. Quat. Sci. Rev. 242, 106443 (2020).Article 

Google Scholar 
Schulte, S. & Müller, P. J. Variations of sea surface temperature and primary productivity during Heinrich and Dansgaard-Oeschger events in the northeastern Arabian Sea. Geo-Mar. Lett. 21, 168–175 (2001).ADS 
Article 

Google Scholar 
Deplazes, G. et al. Weakening and strengthening of the Indian monsoon during Heinrich events and Dansgaard-Oeschger oscillations. Paleoceanography 29, 99–114 (2014).ADS 
Article 

Google Scholar 
Duprey, N. et al. Calibration of seawater temperature and δ18Oseawater signals in Tridacna maxima’s δ18Oshell record based on in situ data. Coral Reefs 34, 437–450 (2015).ADS 
Article 

Google Scholar 
Govil, P. & Naidu, P. D. Evaporation-precipitation changes in the eastern Arabian Sea for the last 68 ka: Implications on monsoon variability. Paleoceanography 25, 1210 (2010).ADS 
Article 

Google Scholar 
Watanabe, T. K. et al. Corals reveal an unprecedented decrease of Arabian Sea upwelling during the current warming era. Geophys. Res. Lett. 48, e2021GL092432 (2021).ADS 
Article 

Google Scholar 
Gaye, B. et al. Glacial−interglacial changes and Holocene variations in Arabian Sea denitrification. Biogeosciences 15, 507–527 (2018).ADS 
CAS 
Article 

Google Scholar 
DiNezio, P. N. et al. Glacial changes in tropical climate amplified by the Indian Ocean. Sci. Adv. 4, 9658 (2018).ADS 
Article 

Google Scholar 
Kleypas, J. A., McManus, J. W. & Menez, L. A. B. Environmental limits to coral reef development: Where do we draw the line? Am. Zool. 39, 146–159 (1999).Article 

Google Scholar 
Abram, N. J., Webster, J. M., Davies, P. J. & Dullo, W. C. Biological response of coral reefs to sea surface temperature variation: Evidence from the raised Holocene reefs of Kikai-jima (Ryukyu Islands, Japan). Coral Reefs 20, 221–234 (2001).Article 

Google Scholar 
Clemens, S. C. & Prell, W. L. A 350,000 year summer-monsoon multi-proxy stack from the Owen Ridge, Northern Arabian Sea. Mar. Geol. 201, 35–51 (2003).ADS 
Article 

Google Scholar 
Caley, T. et al. New Arabian Sea records help decipher orbital timing of Indo-Asian monsoon. Earth Planet. Sci. Lett. 308, 433–444 (2011).ADS 
CAS 
Article 

Google Scholar 
Banakar, V. K., Mahesh, B. S., Burr, G. & Chondankar, A. R. Climatology of the Eastern Arabian Sea during the last glacial cycle reconstructed from paired measurement of foraminiferal δ18O and Mg/Ca. Quat. Res. 73, 535–540 (2010).CAS 
Article 

Google Scholar 
Mattern, F. et al. Coastal dynamics of uplifted and emerged late Pleistocene near-shore coral patch reefs at Fins (eastern coastal Oman, Gulf of Oman). J. Afr. Earth Sci. 138, 192–200 (2018).Article 

Google Scholar 
Hoffmann, J. S., Clark, P. U., Parnell, A. C. & He, F. Regional and global sea-surface temperatures during the last interglaciation. Science 355, 276–279 (2017).ADS 
Article 

Google Scholar 
van de Berg, W. J., van den Broeke, M., Ettema, J., van Meijgaard, E. & Kaspar, F. Significant contribution of insolation to Eemian melting of the Greenland ice sheet. Nat. Geosci. 4, 1245 (2011).
Google Scholar 
Nicholl, J. A. L. et al. A Laurentide outburst flooding event during the last interglacial period. Nat. Geosci. 5, 901–904 (2012).ADS 
CAS 
Article 

Google Scholar 
Tzedenakis, P. C. et al. Enhanced climate instability in the North Atlantic and southern Europe during the Last Interglacial. Nat. Commun. 9, 4235 (2018).ADS 
Article 

Google Scholar 
Sandeep, N. et al. South Asian monsoon response to weakening of Atlantic meridional overturning circulation in a warming climate. Clim. Dyn. 54, 3507–3524 (2020).Article 

Google Scholar 
Rao, S. A. et al. Why is Indian Ocean warming consistently? Clim. Change 110, 709–719 (2012).ADS 
Article 

Google Scholar 
Heron, S. F., Maynard, J. A., van Hooidonk, R. & Eakin, M. Warming trends and bleaching stress of the world’s coral reefs 1985–2012. Sci. Rep. 6, 38402 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Chollett, I., Mumby, P. J. & Cortés, J. Upwelling areas do not guarantee refuge for coral reefs in a warming ocean. Mar. Ecol. Prog. Ser. 416, 47–56 (2010).ADS 
Article 

Google Scholar 
Praveen, V., Ajayamohan, R. S., Valsala, V. & Sandeep, S. Intensification of upwelling along Oman coast in a warming scenario. Geophys. Res. Lett. 43, 7581–7589 (2016).ADS 
Article 

Google Scholar 
Schulz, K. G., Hartley, S. & Eyre, B. Upwelling amplifies ocean acidification on the East Australian Shelf: Implications for marine ecosystems. Front. Mar. Sci. 6, 636 (2019).Article 

Google Scholar 
Southon, J., Kashgarian, M., Fontugne, M., Metivier, B. & Yim, W.W.-S. Marine reservoir corrections for the Indian Ocean and Southeast Asia. Radiocarbon 44, 167–180 (2002).Article 

Google Scholar 
Jochum, K. P., Stoll, B., Herwig, K. & Willbold, M. Validation of LA-ICP-MS trace element analysis of geological glasses using a new solid-state 193 nm Nd:YAG laser and matrix-matched calibration. J. Anal. At. Spectrom. 22, 112–121 (2007).CAS 
Article 

Google Scholar 
Mischel, S. A., Mertz-Kraus, R., Jochum, K. P. & Scholz, D. Termite: An R script for fast reduction laser ablation inductivity coupled plasma mass spectrometry data and its application to trace element measurements. Rapid Commun. Mass Spectrom. 31, 1079–1087 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Jochum, K. P., Willbold, M., Raczek, I., Stoll, B. & Herwig, K. Chemical characterisation of the USGS reference glasses GSA-1G, GSC-1G, GSD-1G, GSE-1G, BCR-2G, BHVO-2G and BIR-1G using EPMA, ID-TIMS, ID-ICP-MS and LA-ICP-MS. Geostand. Geoanal. Res. 29, 285–302 (2005).CAS 
Article 

Google Scholar 
Okai, T., Suzuki, A., Kawahata, H., Terashima, S. & Imai, N. Preparation of a new geological survey of Japan geochemical reference material: Coral JCp-1. Geostand. Newslett. 26, 95–99 (2002).CAS 
Article 

Google Scholar 
Sekimoto, S. et al. Neutron activation analysis of carbonate reference materials: Coral (JCp-1) and giant clam (JCt-1). J. Radioanal. Nucl. Chem. 322, 1579–1583 (2019).CAS 
Article 

Google Scholar 
Paillard, D., Labeyrie, L. & Yiou, P. Macintosh program performs time-series analysis. Eos Trans. AGU 77, 379 (1996).ADS 
Article 

Google Scholar  More

Saba GK, Fraser WR, Saba VS, Iannuzzi RA, Coleman KE, Doney SC, et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat Commun. 2014;5:4318.CAS 
PubMed 
Article 

Google Scholar 
Behrenfeld MJ, Randerson JT, McClain CR, Feldman GC, Los SO, Tucker CJ, et al. Biospheric primary production during an ENSO transition. Science. 2001;291:2594–7.CAS 
PubMed 
Article 

Google Scholar 
Amin SA, Parker MS, Armbrust EV. Interactions between diatoms and bacteria. Microbiol Mol Biol Rev. 2012;76:667–84.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cho BC, Azam F. Major role of bacteria in biogeochemical fluxes in the ocean’s interior. Nature. 1988;332:441–3.CAS 
Article 

Google Scholar 
Amin S, Hmelo L, Van Tol H, Durham B, Carlson L, Heal K, et al. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature. 2015;522:98–101.CAS 
PubMed 
Article 

Google Scholar 
Durham BP, Sharma S, Luo H, Smith CB, Amin SA, Bender SJ, et al. Cryptic carbon and sulfur cycling between surface ocean plankton. Proc Natl Acad Sci. 2015;112:453–7.CAS 
PubMed 
Article 

Google Scholar 
Mühlenbruch M, Grossart HP, Eigemann F, Voss M. Mini‐review: Phytoplankton‐derived polysaccharides in the marine environment and their interactions with heterotrophic bacteria. Environ Microbiol. 2018;20:2671–85.PubMed 
Article 

Google Scholar 
Seymour JR, Amin SA, Raina J-B, Stocker R. Zooming in on the phycosphere: the ecological interface for phytoplankton–bacteria relationships. Nat Microbiol. 2017;2:1–12.Article 

Google Scholar 
Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil L-A, Thingstad F. The ecological role of water-column microbes in the sea. Marine ecology progress series. 1983;10:257–63.Ratnarajah L, Blain S, Boyd PW, Fourquez M, Obernosterer I, Tagliabue A. Resource colimitation drives competition between phytoplankton and bacteria in the Southern Ocean. Geophys Res Lett. 2021;48:e2020GL088369.PubMed 
PubMed Central 
Article 

Google Scholar 
Oulhen N, Schulz BJ, Carrier TJ. English translation of Heinrich Anton de Bary’s 1878 speech, ‘Die Erscheinung der Symbiose’ (‘De la symbiose’). Symbiosis. 2016;69:131–9.Article 

Google Scholar 
Cooper MB, Smith AG. Exploring mutualistic interactions between microalgae and bacteria in the omics age. Curr Opin Plant Biol. 2015;26:147–53.PubMed 
Article 

Google Scholar 
Croft MT, Lawrence AD, Raux-Deery E, Warren MJ, Smith AG. Algae acquire vitamin B12 through a symbiotic relationship with bacteria. Nature. 2005;438:90–3.CAS 
PubMed 
Article 

Google Scholar 
Cole JJ. Interactions between bacteria and algae in aquatic ecosystems. Ann Rev Ecol Syst. 1982;13:291–314.Article 

Google Scholar 
Durham B. Deciphering metabolic currencies that support marine microbial networks. mSystems. 2021;6:e00763-21.Bell W, Mitchell R. Chemotactic and growth responses of marine bacteria to algal extracellular products. Biol Bull. 1972;143:265–77.Article 

Google Scholar 
Baker LJ, Kemp PF. Exploring bacteria–diatom associations using single-cell whole genome amplification. Aquat Microb Ecol. 2014;72:73–88.Article 

Google Scholar 
Graff JR, Rines JE, Donaghay PL. Bacterial attachment to phytoplankton in the pelagic marine environment. Mar Ecol Prog Ser. 2011;441:15–24.Article 

Google Scholar 
Baker LJ, Alegado RA, Kemp PF. Response of diatom-associated bacteria to host growth state, nutrient concentrations, and viral host infection in a model system. Environ Microbiol Rep. 2016;8:917–27.PubMed 
Article 

Google Scholar 
Shibl AA, Isaac A, Ochsenkühn MA, Cárdenas A, Fei C, Behringer G, et al. Diatom modulation of select bacteria through use of two unique secondary metabolites. Proc Natl Acad Sci. 2020;117:27445–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Leinweber K, Kroth PG. Capsules of the diatom Achnanthidium minutissimum arise from fibrillar precursors and foster attachment of bacteria. PeerJ. 2015;3:e858.PubMed 
PubMed Central 
Article 

Google Scholar 
Guo S, Stevens CA, Vance TDR, Olijve LLC, Graham LA, Campbell RL, et al. Structure of a 1.5-MDa adhesin that binds its Antarctic bacterium to diatoms and ice. Sci Adv. 2017;3:e1701440.PubMed 
PubMed Central 
Article 

Google Scholar 
Rao D, Webb JS, Kjelleberg S. Microbial colonization and competition on the Marine Alga Ulva australis. Appl Environ Microbiol. 2006;72:5547–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhou J, Chen G-F, Ying K-Z, Jin H, Song J-T, Cai Z-H, et al. Phycosphere microbial succession patterns and assembly mechanisms in a marine Dinoflagellate bloom. Appl Environ Microbiol. 2019;85:e00349–19.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Seyedsayamdost MR, Case RJ, Kolter R, Clardy J. The Jekyll-and-Hyde chemistry of Phaeobacter gallaeciensis. Nat Chem. 2011;3:331–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Frölicher TL, Sarmiento JL, Paynter DJ, Dunne JP, Krasting JP, Winton M. Dominance of the Southern Ocean in anthropogenic carbon and heat uptake in CMIP5 models. J Clim. 2015;28:862–86.Article 

Google Scholar 
Strzepek RF, Hunter KA, Frew RD, Harrison PJ, Boyd PW. Iron‐light interactions differ in Southern Ocean phytoplankton. Limnol Oceanogr. 2012;57:1182–200.CAS 
Article 

Google Scholar 
Andrew SM, Strzepek RF, M Whitney S, Chow WS, Ellwood MJ. Divergent physiological and molecular responses of light‐and iron‐limited Southern Ocean phytoplankton. Limnol Oceanogr Lett. 2022;7:150–8.CAS 
Article 

Google Scholar 
Bertrand EM, Saito MA, Rose JM, Riesselman CR, Lohan MC, Noble AE, et al. Vitamin B12 and iron colimitation of phytoplankton growth in the Ross Sea. Limnol Oceanogr. 2007;52:1079–93.CAS 
Article 

Google Scholar 
Bertrand EM, McCrow JP, Moustafa A, Zheng H, McQuaid JB, Delmont TO, et al. Phytoplankton–bacterial interactions mediate micronutrient colimitation at the coastal Antarctic sea ice edge. Proc Natl Acad Sci. 2015;112:9938–43.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bates SSB, Hubbard KA, Lundholm N, Montresor M, Leaw CP. Pseudo-nitzschia, Nitzschia, and domoic acid: new research since 2011. Harmful Algae. 2018;79:3–43.PubMed 
Article 

Google Scholar 
Almandoz GO, Ferreyra GA, Schloss IR, Dogliotti AI, Rupolo V, Paparazzo FE, et al. Distribution and ecology of Pseudo-nitzschia species (Bacillariophyceae) in surface waters of the Weddell Sea (Antarctica). Polar Biol. 2008;31:429–42.Article 

Google Scholar 
Jabre LJ, Allen AE, McCain JSP, McCrow JP, Tenenbaum N, Spackeen JL, et al. Molecular underpinnings and biogeochemical consequences of enhanced diatom growth in a warming Southern Ocean. Proc Natl Acad Sci. 2021;118:e2107238118.Malviya S, Scalco E, Audic S, Vincent F, Veluchamy A, Poulain J, et al. Insights into global diatom distribution and diversity in the world’s ocean. Proc Natl Acad Sci. 2016;113:E1516–25.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Moreno CM, Lin Y, Davies S, Monbureau E, Cassar N, Marchetti A. Examination of gene repertoires and physiological responses to iron and light limitation in Southern Ocean diatoms. Polar Biol. 2018;41:679–96.Article 

Google Scholar 
Ellis KA, Cohen NR, Moreno C, Marchetti A. Cobalamin-independent methionine synthase distribution and influence on vitamin B12 growth requirements in marine diatoms. Protist. 2017;168:32–47.CAS 
PubMed 
Article 

Google Scholar 
Price NM, Harrison GI, Hering JG, Hudson RJ, Nirel PM, Palenik B, et al. Preparation and chemistry of the artificial algal culture medium Aquil. Biol Oceanogr. 1989;6:443–61.Article 

Google Scholar 
Hubbard KA, Rocap G, Armbrust EV. Inter- and intraspecific community structure within the diatom genus Pseudo-nitzschia (Bacillariophyceae). J Phycol. 2008;44:637–49.CAS 
Article 

Google Scholar 
Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019;47:W636–41.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.CAS 
PubMed 
Article 

Google Scholar 
Brand LE, Guillard RR, Murphy LS. A method for the rapid and precise determination of acclimated phytoplankton reproduction rates. J Plankton Res. 1981;3:193–201.Article 

Google Scholar 
Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189–91.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nguyen L-T, Schmidt HA, Von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.CAS 
PubMed 
Article 

Google Scholar 
Kalyaanamoorthy S, Minh BQ, Wong TK, Von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14:587–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Trifinopoulos J, Nguyen L-T, von Haeseler A, Minh BQ. W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res. 2016;44:W232–5.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hoang DT, Chernomor O, Von Haeseler A, Minh BQ, Vinh LS. UFBoot2: improving the ultrafast bootstrap approximation. Mol Biol Evol. 2018;35:518–22.CAS 
PubMed 
Article 

Google Scholar 
Letunic I, Bork P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 2019;47:W256–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rodriguez-R LM, Gunturu S, Harvey WT, Rosselló-Mora R, Tiedje JM, Cole JR, et al. The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level. Nucl Acids Res. 2018;46:W282–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:1–8.Article 

Google Scholar 
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.CAS 
PubMed 
Article 

Google Scholar 
Noble RT, Fuhrman JA. Use of SYBR Green I for rapid epifluorescence counts of marine viruses and bacteria. Aquat Microb Ecol. 1998;14:113–8.Article 

Google Scholar 
Alcamán-Arias ME, Fuentes-Alburquenque S, Vergara-Barros P, Cifuentes-Anticevic J, Verdugo J, Polz M, et al. Coastal bacterial community response to glacier melting in the Western Antarctic Peninsula. Microorganisms. 2021;9:88.PubMed Central 
Article 

Google Scholar 
Bowman JP, Gosink JJ, McCAMMON SA, Lewis TE, Nichols DS, Nichols PD, et al. Colwellia demingiae sp. nov., Colwellia hornerae sp. nov., Colwellia rossensis sp. nov. and Colwellia psychrotropica sp. nov.: psychrophilic Antarctic species with the ability to synthesize docosahexaenoic acid (22: ω63). Int J Syst Evol Microbiol. 1998;48:1171–80.CAS 

Google Scholar 
Reisch CR, Moran MA, Whitman WB. Bacterial catabolism of dimethylsulfoniopropionate (DMSP). Front Microbiol. 2011;2:172.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Diaz J, Ingall E, Benitez-Nelson C, Paterson D, de Jonge MD, McNulty I, et al. Marine polyphosphate: a key player in geologic phosphorus sequestration. Science. 2008;320:652–5.CAS 
PubMed 
Article 

Google Scholar 
Nichols CM, Bowman JP, Guezennec J. Olleya marilimosa gen. nov., sp. nov., an exopolysaccharide-producing marine bacterium from the family Flavobacteriaceae, isolated from the Southern Ocean. Int J Syst Evol Microbiol. 2005;55:1557–61.CAS 
PubMed 
Article 

Google Scholar 
von Scheibner M, Sommer U, Jürgens K. Tight coupling of Glaciecola spp. and diatoms during cold-water Phytoplankton spring blooms. Front Microbiol. 2017;8:27.Holmstrom C, Kjelleberg S. Marine Pseudoalteromonas species are associated with higher organisms and produce biologically active extracellular agents. FEMS Microbiol Ecol. 1999;30:285–93.CAS 
PubMed 
Article 

Google Scholar 
Methe BA, Nelson KE, Deming JW, Momen B, Melamud E, Zhang X, et al. The psychrophilic lifestyle as revealed by the genome sequence of Colwellia psychrerythraea 34H through genomic and proteomic analyses. Proc Natl Acad Sci. 2005;102:10913–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kirchman DL. The ecology of Cytophaga–Flavobacteria in aquatic environments. FEMS Microbiol Ecol. 2002;39:91–100.CAS 
PubMed 

Google Scholar 
Hong Z, Lai Q, Luo Q, Jiang S, Zhu R, Liang J, et al. Sulfitobacter pseudonitzschiae sp. nov., isolated from the toxic marine diatom Pseudo-nitzschia multiseries. Int J Syst Evol Microbiol. 2015;65:95–100.CAS 
PubMed 
Article 

Google Scholar 
Brussaard CPD, Riegman R. Influence of bacteria on phytoplankton cell mortality with phosphorus or nitrogen as the algal-growth-limiting nutrient. Aqua Microb Ecol. 1998;14:271–80.Article 

Google Scholar 
Cohen NR, A. Ellis K, Burns WG, Lampe RH, Schuback N, Johnson Z, et al. Iron and vitamin interactions in marine diatom isolates and natural assemblages of the Northeast Pacific Ocean. Limnol Oceanogr. 2017;62:2076–96.CAS 
Article 

Google Scholar 
Hunken M, Harder J, Kirst G. Epiphytic bacteria on the Antarctic ice diatom Amphiprora kufferathii Manguin cleave hydrogen peroxide produced during algal photosynthesis. Plant Biol. 2008;10:519–26.CAS 
PubMed 
Article 

Google Scholar 
Gourinchas G, Etzl S, Winkler A. Bacteriophytochromes–from informative model systems of phytochrome function to powerful tools in cell biology. Curr Opin Struct Biol. 2019;57:72–83.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gourion B, Rossignol M, Vorholt JA. A proteomic study of Methylobacterium extorquens reveals a response regulator essential for epiphytic growth. Proc Natl Acad Sci. 2006;103:13186–91.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mukherjee S, Bassler BL. Bacterial quorum sensing in complex and dynamically changing environments. Nat Rev Microbiol. 2019;17:371–82.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dong YH, Zhang LH. Quorum sensing and quorum-quenching enzymes. J Microbiol. 2005;43:101–9.CAS 
PubMed 

Google Scholar 
Núñez-Montero K, Barrientos L. Advances in Antarctic research for antimicrobial discovery: a comprehensive narrative review of bacteria from Antarctic environments as potential sources of novel antibiotic compounds against human pathogens and microorganisms of industrial importance. Antibiotics. 2018;7:90.Kieft B, Li Z, Bryson S, Hettich RL, Pan C, Mayali X, et al. Phytoplankton exudates and lysates support distinct microbial consortia with specialized metabolic and ecophysiological traits. Proc Natl Acad Sci. 2021;118:e2101178118.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Maranger R, Bird DF. Viral abundance in aquatic systems: a comparison between marine and fresh waters. Mar Ecol Prog Ser. 1995;121:217–26.Article 

Google Scholar 
Sharpe GC, Gifford SM, Septer AN. A model roseobacter, Ruegeria pomeroyi DSS-3, employs a diffusible killing mechanism to eliminate competitors. Msystems. 2020;5:e00443–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cude WN, Mooney J, Tavanaei AA, Hadden MK, Frank AM, Gulvik CA, et al. Production of the antimicrobial secondary metabolite indigoidine contributes to competitive surface colonization by the marine roseobacter Phaeobacter sp. strain Y4I. Appl Environ Microbiol. 2012;78:4771–80.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Long RA, Rowley DC, Zamora E, Liu J, Bartlett DH, Azam F. Antagonistic interactions among marine bacteria impede the proliferation of Vibrio cholerae. Appl Environ Microbiol. 2005;71:8531–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bruhn JB, Gram L, Belas R. Production of antibacterial compounds and biofilm formation by Roseobacter species are influenced by culture conditions. Appl Environ Microbiol. 2007;73:442–50.CAS 
PubMed 
Article 

Google Scholar 
Gromek SM, Suria AM, Fullmer MS, Garcia JL, Gogarten JP, Nyholm SV, et al. Leisingera sp. JC1, a bacterial isolate from Hawaiian bobtail squid eggs, produces indigoidine and differentially inhibits vibrios. Front Microbiol. 2016;7:1342.PubMed 
PubMed Central 
Article 

Google Scholar 
Sharifah EN, Eguchi M. The phytoplankton Nannochloropsis oculata enhances the ability of Roseobacter clade bacteria to inhibit the growth of fish pathogen Vibrio anguillarum. PLoS One. 2011;6:e26756.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kerwin AH, Gromek SM, Suria AM, Samples RM, Deoss DJ, O’Donnell K, et al. Shielding the next generation: symbiotic bacteria from a reproductive organ protect bobtail squid eggs from fungal fouling. MBio. 2019;10:e02376–19.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tonelli M, Signori CN, Bendia A, Neiva J, Ferrero B, Pellizari V, et al. Climate projections for the southern ocean reveal impacts in the marine microbial communities following increases in sea surface temperature. Front Mar Sci. 2021;8:636226.Andrew SM, Morell HT, Strzepek RF, Boyd PW, Ellwood MJ. Iron availability influences the tolerance of southern ocean phytoplankton to warming and elevated irradiance. Front Mar Sci. 2019;6:681.Andrew SM, Strzepek RF, Branson O, Ellwood MJ. Ocean acidification reduces the growth of two Southern Ocean phytoplankton. Mar Ecol Prog Ser. 2022;682:51–64.CAS 
Article 

Google Scholar 
Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Weezel GP, Medema MH, et al. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucl Acids Res. 2021;49:W29–35.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ferrer-González FX, Widner B, Holderman NR, Glushka J, Edison AS, Kujawinski EB, et al. Resource partitioning of phytoplankton metabolites that support bacterial heterotrophy. ISME J. 2021;15:762–73.PubMed 
Article 

Google Scholar  More

Bryant, S. V., Endo, T. & Gardiner, D. M. Vertebrate limb regeneration and the origin of limb stem cells. Int. J. Dev. Biol. 46, 887–896 (2004).
Google Scholar 
Fleming, P. A., Muller, D. & Bateman, P. W. Leave it all behind: A taxonomic perspective of autotomy in invertebrates. Biol. Rev. 82, 481–510 (2007).PubMed 
Article 

Google Scholar 
Bely, A. E. & Nyberg, K. G. Evolution of animal regeneration: Re-emergence of a field. Trends Ecol. Evol. 25, 161–170 (2010).PubMed 
Article 

Google Scholar 
Lindsay, S. M. Frequency of injury and the ecology of regeneration in marine benthic invertebrates. Integr. Comp. Biol. 50, 479–493 (2010).PubMed 
Article 

Google Scholar 
Wilson, B. S. Tail injuries increase the risk of mortality in free-living lizards (Uta stansburiana). Oecologia 92, 145–152 (1992).ADS 
PubMed 
Article 

Google Scholar 
Chapple, D. G. & Swain, R. Inter-populational variation in the cost of autotomy in the metallic skink (Niveoscincus metallicus). J. Zool. 264, 411–418 (2004).Article 

Google Scholar 
Tyler, R. K., Winchell, K. M. & Revell, L. J. Tails of the city: Caudal autotomy in the tropical lizard, Anolis cristatellus, in urban and natural areas of Puerto Rico. J. Herpetol. 50, 435–441 (2016).Article 

Google Scholar 
Griffen, B. D., Cannizzo, Z. J., Carver, J. & Meidell, M. Reproductive and energetic costs of injury in the mangrove tree crab. Mar. Ecol. Prog. Ser. 640, 127–137 (2020).ADS 
Article 

Google Scholar 
Smith, L. D. & Hines, A. H. Autotomy in blue crab (Callinectes sapidus Rathbun) populations: Geographic, temporal, and ontogenetic variation. Biol. Bull. 180, 416–431 (1991).CAS 
PubMed 
Article 

Google Scholar 
Maginnis, T. L. The costs of autotomy and regeneration in animals: A review and framework for future research. Behav. Ecol. 17, 857–872 (2006).Article 

Google Scholar 
Suma Gupta, N. V., Kurup, K. N. P., Adiyodi, R. G. & Adiyodi, K. G. The antagonism between somatic growth and testicular activity during different phases in intermoult (stage C4) in sexually mature freshwater crab, Paratelphusa hydrodromous. Invertebr. Reprod. Dev. 16, 195–203 (1989).Article 

Google Scholar 
Devi, S. & Adiyodi, R. G. Effect of multiple limb autotomy on oogenesis and somatic growth in Paratelphusa hydromous. Trop. Freshw. Biol. 9, 43–56 (2000).
Google Scholar 
Juanes, F. & Smith, L. D. The ecological consequences of limb damage and loss in decapod crustaceans: A review and prospectus. J. Exp. Mar. Biol. Ecol. 193, 197–223 (1995).Article 

Google Scholar 
Cheng, J. H. & Chang, E. S. Determinants of postmolt size in the American lobster (Homarus americanus). I. D13 is the critical stage. Can. J. Fish. Aquat. Sci. 50, 2106–2111 (1993).Article 

Google Scholar 
Kuris, A. M. & Mager, M. Effect of limb regeneration on size increase at molt of the shore crabs Hemigrapsus oregonensis and Pachygrapsus crassipes. J. Exp. Zool. 193, 353–359 (1975).CAS 
PubMed 
Article 

Google Scholar 
Ballinger, R. E. & Tinkle, D. W. On the cost of tail regeneration to body growth in lizards. J. Herpetol. 13, 374–375 (1979).Article 

Google Scholar 
Hopkins, P. M. & Das, S. Regeneration in crustaceans. Nat. Hist. Crustacea 4, 168–198 (2015).
Google Scholar 
Lai, A. G. & Aboobaker, A. A. EvoRegen in animals: Time to uncover deep conservation or convergence of adult stem cell evolution and regenerative processes. Dev. Biol. 433, 118–131 (2018).CAS 
PubMed 
Article 

Google Scholar 
Boudreau, S. A. & Worm, B. Ecological role of large benthic decapods in marine ecosystems: A review. Mar. Ecol. Prog. Ser. 469, 195–213 (2012).ADS 
Article 

Google Scholar 
Turner, J. T. The importance of small planktonic copepods and their roles in pelagic marine food webs. Zool. Stud. 43, 255–266 (2004).
Google Scholar 
Bondad-Reantaso, M. G., Subasinghe, R. P., Josupeit, H., Cai, J. & Zhou, X. The role of crustacean fisheries and aquaculture in global food security: Past, present and future. J. Invertebr. Pathol. 110, 158–165 (2012).PubMed 
Article 

Google Scholar 
Galil, B. S., Clark, P. F. & Carleton, J. T. In the Wrong Place—Alien Marine Crustaceans: Distribution, Biology, and Impacts (Springer, 2011).Book 

Google Scholar 
Gallien, L., Münkemüller, T., Albert, C. H., Boulangeat, I. & Thuiller, W. Predicting potential distributions of invasive species: Where to go from here?. Divers. Distrib. 16, 331–342 (2010).Article 

Google Scholar 
Barbet-Massin, M., Rome, Q., Villemant, C. & Courchamp, F. Can species distribution models really predict the expansion of invasive species?. PLoS One 13, e0193085 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Griffen, B. D., van den Akker, D., DiNuzzo, E. R., Anderson, L. & Vernier, A. Comparing methods for predicting the impacts of invasive species. Biol. Invasions 23, 491–505 (2021).Article 

Google Scholar 
Williams, A. B. & McDermott, J. J. An eastern United States record for the western Indo-Pacific crab, Hemigrapsus sanguineus (Crustacea: Decapoda: Grapsidae). Proc. Biol. Soc. Wash. 103, 108–109 (1990).
Google Scholar 
Blakeslee, A. M. et al. Reconstructing the invasion history of the Asian shorecrab, Hemigrapsus sanguineus (De Haan 1835) in the Western Atlantic. Mar. Biol. 164, 1–19 (2017).
Google Scholar 
Griffen, B. D. & Delaney, D. G. Species invasion shifts the importance of predator dependence. Ecology 88, 3012–3021 (2007).PubMed 
Article 

Google Scholar 
Epifanio, C. E. Invasion biology of the Asian shore crab Hemigrapsus sanguineus: A review. J. Exp. Mar. Biol. Ecol. 441, 33–49 (2013).Article 

Google Scholar 
Gerard, V. A., Cerrato, R. M. & Larson, A. A. Potential impacts of a western Pacific grapsid crab on intertidal communities of the northwestern Atlantic Ocean. Biol. Invasions 1, 353–361 (1999).Article 

Google Scholar 
Kraemer, G. P., Sellberg, M., Gordon, A. & Main, J. Eight-year record of Hemigrapsus sanguineus (Asian shore crab) invasion in western Long Island Sound estuary. Northeast. Nat. 14, 207–224 (2007).Article 

Google Scholar 
Davis, J. L. et al. Autotomy in the Asian shore crab (Hemigrapsus sanguineus) in a non-native area of its range. J. Crust. Biol. 25, 655–660 (2005).Article 

Google Scholar 
Delaney, D. G., Griffen, B. D. & Leung, B. Does consumer injury modify invasion impact?. Biol. Invasions 13, 2935–2945 (2011).Article 

Google Scholar 
Jensen, G. C., McDonald, P. S. & Armstrong, D. A. East meets west: Competitive interactions between green crab Carcinus maenas, and native and introduced shore crab Hemigrapsus spp. Mar. Ecol. Prog. Ser. 225, 251–262 (2002).ADS 
Article 

Google Scholar 
Lohrer, A. M. & Whitlatch, R. B. Interactions among aliens: Apparent replacement of one exotic species by another. Ecology 83, 719–732 (2002).Article 

Google Scholar 
Griffen, B. D. & Williamson, T. Influence of predator density on nonindependent effects of multiple predator species. Oecologia 155, 151–159 (2008).ADS 
PubMed 
Article 

Google Scholar 
Vernier, A. & Griffen, B. D. Physiological effects of limb loss on the Asian shore crab Hemigrapsus sanguineus. Northeast. Nat. 26, 761–771 (2019).Article 

Google Scholar 
Lohrer, A. M. & Whitlatch, R. B. Relative impacts of two exotic brachyuran species on blue mussel populations in Long Island Sound. Mar. Ecol. Prog. Ser. 227, 135–144 (2002).ADS 
Article 

Google Scholar 
Goldstein, J. S. & Carloni, J. T. Assessing the implications of live claw removal on Jonah crab (Cancer borealis), an emerging fishery in the Northwest Atlantic. Fish. Res. 243, 106046 (2021).Article 

Google Scholar 
Hines, A. H. Allometric constraints and variables of reproductive effort in brachyuran crabs. Mar. Biol. 69, 309–320 (1982).Article 

Google Scholar 
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 
Article 

Google Scholar 
Sokolova, I. M. Energy-limited tolerance to stress as a conceptual framework to integrate the effects of multiple stressors. Integr. Comp. Biol. 53, 597–608 (2013).PubMed 
Article 

Google Scholar 
Prestholdt, T. et al. Tradeoffs associated with autotomy and regeneration and their potential role in the evolution of regenerative abilities. Behav. Ecol. 33, 518–525 (2022).Article 

Google Scholar 
McDermott, J. J. The western Pacific brachyuran Hemigrapsus sanguineus (Grapsidae) in its new habitat along the Atlantic coast of the United States: Reproduction. J. Crustac. Biol. 18, 308–316 (1998).Article 

Google Scholar 
Depledge, M. H. Hemigrapsus sanguineus (De Haan). Asian Mar. Biol. 1, 115–123 (1984).
Google Scholar 
Saigusa, M. & Kawagoye, O. Circatidal rhythm of an intertidal crab, Hemigrapsus sanguineus: Synchrony with unequal tide height and involvement of a light-response mechanism. Mar. Biol. 129, 87–96 (1997).Article 

Google Scholar 
Choy, S. C. A rapid method for removing and counting eggs from fresh and preserved decapod crustaceans. Aquaculture 48, 369–372 (1985).Article 

Google Scholar 
Rosa, R., Calado, R., Narciso, L. & Nunes, M. L. Embryogenesis of decapod crustaceans with different life history traits, feeding ecologies and habitats: A fatty acid approach. Mar. Biol. 151, 935–947 (2007).Article 

Google Scholar 
Griffen, B. D. & Mosblack, H. Predicting diet and consumption rate differences between and within species using gut ecomorphology. J. Anim. Ecol. 80, 854–863 (2011).PubMed 
Article 

Google Scholar 
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Zero-truncated and zero-inflated models for count data. In Mixed Effects Models and Extensions in Ecology with R 261–293 (Springer, 2009).MATH 
Chapter 

Google Scholar 
Griffen, B. D. Linking individual diet variation and fecundity in an omnivorous marine consumer. Oecologia 174, 121–130 (2014).ADS 
PubMed 
Article 

Google Scholar  More

Pedros-Alio C. The rare bacterial biosphere. Ann Rev Mar Sci. 2012;4:449–66. https://doi.org/10.1146/annurev-marine-120710-100948.Article 
PubMed 

Google Scholar 
Sogin ML, Morrison HG, Huber JA, Welch DM, Huse SM, Neal PR, et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc Natl Acad Sci. 2006;103:12115–20. https://doi.org/10.1073/pnas.0605127103.Article 
PubMed 
PubMed Central 

Google Scholar 
Hausmann B, Pelikan C, Rattei T, Loy A, Pester M. Long-term transcriptional activity at zero growth of a cosmopolitan rare biosphere member. mBio. 2019;10:e02189–18. https://doi.org/10.1128/mBio.02189-18.Article 
PubMed 
PubMed Central 

Google Scholar 
Pester M, Bittner N, Deevong P, Wagner M, Loy AA. ‘Rare biosphere’microorganism contributes to sulfate reduction in a peatland. ISME J. 2010;4:1591–602.Article 

Google Scholar 
Rivett DW, Bell T. Abundance determines the functional role of bacterial phylotypes in complex communities. Nat Microbiol. 2018;3:767–72. https://doi.org/10.1038/s41564-018-0180-0.Article 
PubMed 
PubMed Central 

Google Scholar 
van Elsas JD, Chiurazzi M, Mallon CA, Elhottova D, Kristufek V, Salles JF. Microbial diversity determines the invasion of soil by a bacterial pathogen. Proc Natl Acad Sci USA. 2012;109:1159–64. https://doi.org/10.1073/pnas.1109326109.Article 
PubMed 
PubMed Central 

Google Scholar 
Magurran AE, Henderson PA. Explaining the excess of rare species in natural species abundance distributions. Nature. 2003;422:714–6.Article 

Google Scholar 
Rabinowitz D, Rapp JK, Dixon PM. Competitive abilities of sparse grass species: means of persistence or cause of abundance. Ecology. 1984;65:1144–54. https://doi.org/10.2307/1938322.Article 

Google Scholar 
Reinhardt K, Köhler G, Maas S, Detzel P. Low dispersal ability and habitat specificity promote extinctions in rare but not in widespread species: the Orthoptera of Germany. Ecography. 2005;28:593–602. https://doi.org/10.1111/j.2005.0906-7590.04285.x.Article 

Google Scholar 
Yenni G, Adler PB, Ernest S. Strong self-limitation promotes the persistence of rare species. Ecology. 2012;93:456–61.Article 

Google Scholar 
Jousset A, Bienhold C, Chatzinotas A, Gallien L, Gobet A, Kurm V, et al. Where less may be more: how the rare biosphere pulls ecosystems strings. The ISME J. 2017;11:853–62. https://doi.org/10.1038/ismej.2016.174.Article 
PubMed 

Google Scholar 
Thingstad TF. Elements of a theory for the mechanisms controlling abundance, diversity, and biogeochemical role of lytic bacterial viruses in aquatic systems. Limnol Oceanogr. 2000;45:1320–8. https://doi.org/10.4319/lo.2000.45.6.1320.Article 

Google Scholar 
Szekely AJ, Langenheder S. The importance of species sorting differs between habitat generalists and specialists in bacterial communities. FEMS Microbiol Ecol. 2014;87:102–12. https://doi.org/10.1111/1574-6941.12195.Article 
PubMed 

Google Scholar 
Mo Y, Zhang W, Yang J, Lin Y, Yu Z, Lin S. Biogeographic patterns of abundant and rare bacterioplankton in three subtropical bays resulting from selective and neutral processes. ISME J. 2018;12:2198–210. https://doi.org/10.1038/s41396-018-0153-6.Article 
PubMed 
PubMed Central 

Google Scholar 
Nemergut DR, Schmidt SK, Fukami T, O’Neill SP, Bilinski TM, Stanish LF, et al. Patterns and processes of microbial community assembly. Microbiol Mol Biology Rev. 2013;77:342–56. https://doi.org/10.1128/MMBR.00051-12.Article 

Google Scholar 
Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206. https://doi.org/10.1086/652373.Article 
PubMed 

Google Scholar 
Vellend M The Theory of Ecological Communities. Princeton University Pres. 2016:61-7.Jia X, Dini-Andreote F, Falcao Salles J. Community assembly processes of the microbial rare biosphere. Trends Microbiol. 2018;26:738–47. https://doi.org/10.1016/j.tim.2018.02.011.Article 
PubMed 

Google Scholar 
Stegen JC, Lin X, Fredrickson JK, Chen X, Kennedy DW, Murray CJ, et al. Quantifying community assembly processes and identifying features that impose them. ISME J. 2013;7:2069–79. https://doi.org/10.1038/ismej.2013.93.Article 
PubMed 
PubMed Central 

Google Scholar 
Stegen JC, Lin X, Fredrickson JK, Konopka AE. Estimating and mapping ecological processes influencing microbial community assembly. Front Microbiol. 2015;6:https://doi.org/10.3389/fmicb.2015.00370.Webb CO, Ackerly DD, McPeek MA, Donoghue MJ. Phylogenies and community ecology. Ann Rev Ecol Syst. 2002;33:475–505. https://doi.org/10.1146/annurev.ecolsys.33.010802.150448.Article 

Google Scholar 
Lynch MDJ, Neufeld JD. Ecology and exploration of the rare biosphere. Nat Rev Micro. 2015;13:217–29. https://doi.org/10.1038/nrmicro3400.Article 

Google Scholar 
Dini-Andreote F, Stegen JC, van Elsas JD, Salles JF. Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc Natl Acad Sci USA. 2015;112:E1326–E32. https://doi.org/10.1073/pnas.1414261112.Article 
PubMed 
PubMed Central 

Google Scholar 
Chase JM, Kraft NJB, Smith KG, Vellend M, Inouye BD. Using null models to disentangle variation in community dissimilarity from variation in α-diversity. Ecosphere. 2011;2:art24 https://doi.org/10.1890/es10-00117.1.Article 

Google Scholar 
Shade A, Jones SE, Caporaso JG, Handelsman J, Knight R, Fierer N, et al. Conditionally rare taxa disproportionately contribute to temporal changes in microbial diversity. mBio. 2014;5:e01371–14. https://doi.org/10.1128/mBio.01371-14.Article 
PubMed 
PubMed Central 

Google Scholar 
Strous M, Heijnen JJ, Kuenen JG, Jetten MSM. The sequencing batch reactor as a powerful tool for the study of slowly growing anaerobic ammonium-oxidizing microorganisms. Appl Microbiol Biotechnol. 1998;50:589–96. https://doi.org/10.1007/s002530051340.Article 

Google Scholar 
Goldfarb KC, Karaoz U, Hanson CA, Santee CA, Bradford MA, Treseder KK, et al. Differential growth responses of soil bacterial taxa to carbon substrates of varying chemical recalcitrance. Front Microbiol. 2011;2:94. https://doi.org/10.3389/fmicb.2011.00094.Article 
PubMed 
PubMed Central 

Google Scholar 
Jia X, Dini-Andreote F, Falcao Salles J. Comparing the influence of assembly processes governing bacterial community succession based on DNA and RNA Data. Microorganisms. 2020;8. https://doi.org/10.3390/microorganisms8060798.Olff H, De Leeuw J, Bakker JP, Platerink RJ, van Wijnen HJ. Vegetation succession and herbivory in a salt marsh: changes induced by sea level rise and silt deposition along an elevational gradient. J Ecol. 1997;85:799–814. https://doi.org/10.2307/2960603.Article 

Google Scholar 
Dini-Andreote F, Silva M, Triado-Margarit X, Casamayor EO, van Elsas JD, Salles JF. Dynamics of bacterial community succession in a salt marsh chronosequence: evidences for temporal niche partitioning. ISME J. 2014;8:1989–2001. https://doi.org/10.1038/ismej.2014.54.Article 
PubMed 
PubMed Central 

Google Scholar 
Dini-Andreote F, Pylro VS, Baldrian P, van Elsas JD, Salles JF. Ecological succession reveals potential signatures of marine–terrestrial transition in salt marsh fungal communities. ISME J. 2016;10:1984–97.Article 

Google Scholar 
Schrama M, Berg MP, Olff H. Ecosystem assembly rules: the interplay of green and brown webs during salt marsh succession. Ecology. 2012;93:2353–64.Article 

Google Scholar 
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci. 2011;108:4516–22. https://doi.org/10.1073/pnas.1000080107.Article 
PubMed 

Google Scholar 
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–4.Article 

Google Scholar 
Carini P, Marsden PJ, Leff JW, Morgan EE, Strickland MS, Fierer N. Relic DNA is abundant in soil and obscures estimates of soil microbial diversity. Nat Microbiol. 2016;2:16242. https://doi.org/10.1038/nmicrobiol.2016.242.Article 
PubMed 

Google Scholar 
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet C, Al-Ghalith GA, et al. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ Preprints. 2018;6:e27295v2. https://doi.org/10.7287/peerj.preprints.27295v2.Article 

Google Scholar 
Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017;11:2639–43. https://doi.org/10.1038/ismej.2017.119.Article 
PubMed 
PubMed Central 

Google Scholar 
Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucleic Acids Res. 2014;42:D643–8. https://doi.org/10.1093/nar/gkt1209.Article 
PubMed 

Google Scholar 
Price MN, Dehal PS, Arkin AP. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol. 2009;26:1641–50.Article 

Google Scholar 
R Core Team: R: A language and environment for statistical computing. In. Vienna, Austria: R Foundation for Statistical Computing; 2017.RStudio Team: RStudio: integrated development for R. In., vol. 42. Boston, MA: RStudio, Inc.; 2015.Wickham H. ggplot2: elegant graphics for data analysis. J Stat Softw. 2010;35:65–88.
Google Scholar 
Chen H, Boutros PC. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinf. 2011;12:35.Article 

Google Scholar 
Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14:927–30. https://doi.org/10.1111/j.1654-1103.2003.tb02228.x.Article 

Google Scholar 
Yamamoto K, Hackley KC, Kelly WR, Panno SV, Sekiguchi Y, Sanford RA, et al. Diversity and geochemical community assembly processes of the living rare biosphere in a sand-and-gravel aquifer ecosystem in the Midwestern United States. Sci Rep. 2019;9. https://doi.org/10.1038/s41598-019-49996-z.Galand PE, Casamayor EO, Kirchman DL, Lovejoy C. Ecology of the rare microbial biosphere of the Arctic Ocean. Proc Natl Acad Sci. 2009;106:22427–32. https://doi.org/10.1073/pnas.0908284106.Article 
PubMed 
PubMed Central 

Google Scholar 
Reveillaud J, Maignien L, Murat Eren A, Huber JA, Apprill A, Sogin ML, et al. Host-specificity among abundant and rare taxa in the sponge microbiome. ISME J. 2014;8:1198–209. https://doi.org/10.1038/ismej.2013.227.Article 
PubMed 
PubMed Central 

Google Scholar 
Logares R, Audic S, Bass D, Bittner L, Boutte C, Christen R, et al. Patterns of rare and abundant marine microbial eukaryotes. Curr Biol. 2014;24:813–21. https://doi.org/10.1016/j.cub.2014.02.050.Article 
PubMed 

Google Scholar 
Campbell BJ, Yu L, Heidelberg JF, Kirchman DL. Activity of abundant and rare bacteria in a coastal ocean. Proc Natl Acad Sci. 2011;108:12776–81. https://doi.org/10.1073/pnas.1101405108.Article 
PubMed 
PubMed Central 

Google Scholar 
Hirsch JE. An index to quantify an individual’s scientific research output. Proc Natl Acad Sci USA. 2005;102:16569. https://doi.org/10.1073/pnas.0507655102.Article 
PubMed 
PubMed Central 

Google Scholar 
Haegeman B, Hamelin J, Moriarty J, Neal P, Dushoff J, Weitz JS. Robust estimation of microbial diversity in theory and in practice. ISME J. 2013;7:1092–101. https://doi.org/10.1038/ismej.2013.10.Article 
PubMed 
PubMed Central 

Google Scholar 
Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics (Oxford, England). 2004;20:289–90.Article 

Google Scholar 
Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics. 2010;26:1463–4.Article 

Google Scholar 
Stegen JC, Lin X, Konopka AE, Fredrickson JK. Stochastic and deterministic assembly processes in subsurface microbial communities. ISME J. 2012;6:1653–64. https://doi.org/10.1038/ismej.2012.22.Article 
PubMed 
PubMed Central 

Google Scholar 
Jiao S, Lu Y. Soil pH and temperature regulate assembly processes of abundant and rare bacterial communities in agricultural ecosystems. Environ Microbiol. 2020;22:1052–65. https://doi.org/10.1111/1462-2920.14815.Article 
PubMed 

Google Scholar 
Logares R, Lindström ES, Langenheder S, Logue JB, Paterson H, Laybourn-Parry J, et al. Biogeography of bacterial communities exposed to progressive long-term environmental change. ISME J. 2012;7:937–48. https://doi.org/10.1038/ismej.2012.168.Article 
PubMed 
PubMed Central 

Google Scholar 
Kurm V, van der Putten WH, Weidner S, Geisen S, Snoek BL, Bakx T, et al. Competition and predation as possible causes of bacterial rarity. Environ Microbiol. 2019;21:1356–68. https://doi.org/10.1111/1462-2920.14569.Article 
PubMed 
PubMed Central 

Google Scholar 
Aanderud ZT, Saurey S, Ball BA, Wall DH, Barrett JE, Muscarella ME, et al. Stoichiometric shifts in Soil C:N:P promote bacterial taxa dominance, maintain biodiversity, and deconstruct community assemblages. Front Microbiol. 2018;9:1401 https://doi.org/10.3389/fmicb.2018.01401.Article 
PubMed 
PubMed Central 

Google Scholar 
Sloan WT, Woodcock S, Lunn M, Head IM, Curtis TP. Modeling taxa-abundance distributions in microbial communities using environmental sequence data. Microb Ecol. 2007;53:443–55. https://doi.org/10.1007/s00248-006-9141-x.Article 
PubMed 

Google Scholar 
Magurran AE, McGill BJ. Biological diversity: frontiers in measurement and assessment. Oxford University Press; 2011.Richter-Heitmann T, Hofner B, Krah FS, Sikorski J, Wust PK, Bunk B, et al. Stochastic dispersal rather than deterministic selection explains the spatio-temporal distribution of soil bacteria in a temperate grassland. Front Microbiol. 2020;11:1391. https://doi.org/10.3389/fmicb.2020.01391.Article 
PubMed 
PubMed Central 

Google Scholar 
Ivanov II, Honda K. Intestinal commensal microbes as immune modulators. Cell Host Microbe. 2012;12:496–508. https://doi.org/10.1016/j.chom.2012.09.009.Article 
PubMed 
PubMed Central 

Google Scholar 
van Veelen HPJ, Falcao Salles J, Tieleman BI. Multi-level comparisons of cloacal, skin, feather and nest-associated microbiota suggest considerable influence of horizontal acquisition on the microbiota assembly of sympatric woodlarks and skylarks. Microbiome. 2017;5:156. https://doi.org/10.1186/s40168-017-0371-6.Article 
PubMed 
PubMed Central 

Google Scholar 
Warmink JA, Nazir R, Corten B, van Elsas JD. Hitchhikers on the fungal highway: The helper effect for bacterial migration via fungal hyphae. Soil Biology Biochem. 2011;43:760–5. https://doi.org/10.1016/j.soilbio.2010.12.009.Article 

Google Scholar 
Snell Taylor SJ, Evans BS, White EP, Hurlbert AH. The prevalence and impact of transient species in ecological communities. Ecology. 2018;99:1825–35. https://doi.org/10.1002/ecy.2398.Article 
PubMed 

Google Scholar 
Kurm V, Geisen S, Gera Hol WH. A low proportion of rare bacterial taxa responds to abiotic changes compared with dominant taxa. Environ Microbiol. 2019;21:750–8. https://doi.org/10.1111/1462-2920.14492.Article 
PubMed 

Google Scholar 
Wang Y, Hatt JK, Tsementzi D, Rodriguez RL, Ruiz-Perez CA, Weigand MR, et al. Quantifying the Importance of the Rare Biosphere for Microbial Community Response to Organic Pollutants in a Freshwater Ecosystem. Appl Environ Microbiol. 2017;83:e03321–16. https://doi.org/10.1128/AEM.03321-16.Article 
PubMed 
PubMed Central 

Google Scholar 
Cao J, Jia X, Pang S, Hu Y, Li Y, Wang Q. Functional structure, taxonomic composition and the dominant assembly processes of soil prokaryotic community along an altitudinal gradient. Appl Soil Ecol. 2020;155. https://doi.org/10.1016/j.apsoil.2020.103647.Meyer KM, Memiaghe H, Korte L, Kenfack D, Alonso A, Bohannan BJM. Why do microbes exhibit weak biogeographic patterns. ISME J. 2018;12:1404–13. https://doi.org/10.1038/s41396-018-0103-3.Article 
PubMed 
PubMed Central 

Google Scholar 
Anderson RE, Sogin ML, Baross JA. Biogeography and ecology of the rare and abundant microbial lineages in deep-sea hydrothermal vents. FEMS Microbiol Ecol. 2015;91:1–11. https://doi.org/10.1093/femsec/fiu016.Article 
PubMed 

Google Scholar 
Mallon CA, Le Roux X, van Doorn GS, Dini-Andreote F, Poly F, Salles JF. The impact of failure: unsuccessful bacterial invasions steer the soil microbial community away from the invader’s niche. ISME J. 2018;12:728–41. https://doi.org/10.1038/s41396-017-0003-y.Article 
PubMed 
PubMed Central 

Google Scholar 
Langenheder S, Bulling MT, Solan M, Prosser JI. Bacterial biodiversity-ecosystem functioning relations are modified by environmental complexity. PLoS One. 2010;5:e10834. https://doi.org/10.1371/journal.pone.0010834.Article 
PubMed 
PubMed Central 

Google Scholar 
Bardgett RD, Van Der Putten WH. Belowground biodiversity and ecosystem functioning. Nature. 2014;515:505.Article 

Google Scholar 
Griffiths B, Ritz K, Wheatley R, Kuan H, Boag B, Christensen S, et al. An examination of the biodiversity–ecosystem function relationship in arable soil microbial communities. Soil Biol Biochem. 2001;33:1713–22.Article 

Google Scholar 
Hooper DU, Chapin F, Ewel J, Hector A, Inchausti P, Lavorel S, et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr. 2005;75:3–35.Article 

Google Scholar 
Logares R, Tesson SVM, Canback B, Pontarp M, Hedlund K, Rengefors K. Contrasting prevalence of selection and drift in the community structuring of bacteria and microbial eukaryotes. Environ Microbiol. 2018;20:2231–40. https://doi.org/10.1111/1462-2920.14265.Article 
PubMed 

Google Scholar 
Zhou J, Ning D. Stochastic community assembly: does it matter in microbial ecology? Microbiol Mol Biol Rev. 2017;81:e00002–17.Article 

Google Scholar 
Logares R, Deutschmann IM, Junger PC, Giner CR, Krabberod AK, Schmidt TSB, et al. Disentangling the mechanisms shaping the surface ocean microbiota. Microbiome. 2020;8:55. https://doi.org/10.1186/s40168-020-00827-8.Article 
PubMed 
PubMed Central 

Google Scholar 
Dini-Andreote F, Brossi MJ, van Elsas JD, Salles JF. Reconstructing the genetic potential of the microbially-mediated nitrogen cycle in a salt marsh ecosystem. Front Microbiol. 2016;7:902. https://doi.org/10.3389/fmicb.2016.00902.Article 
PubMed 
PubMed Central 

Google Scholar  More