Replies to Reviewer #1 of paper: gchron‐2020‐5: Resolving the timescales of magmatic and hydrothermal processes associated with porphyry deposit formation using zircon U‐Pb petrochronology

Understanding the formation of economically important porphyry-Cu-Au deposits requires the knowledge of the magmaticto-hydrothermal processes that act within the much larger underlying magmatic system and the timescales on which they occur. We apply high-precision zircon geochronology (CA-ID-TIMS) and spatially resolved zircon geochemistry (LA-ICP-MS) to constrain the magmatic evolution of the underlying magma reservoir at the Pliocene Batu Hijau porphyry-Cu-Au deposit. We 15 then use this extensive dataset to assess the accuracy and precision of different U-Pb dating methods of the same zircon crystals. Emplacement of the oldest preto syn-ore tonalite (3.736 ± 0.023 Ma) and the youngest tonalite porphyry cutting economic Cu-Au mineralisation (3.646 ± 0.022 Ma) is determined by the youngest zircon grain from each sample, which constrains the duration of metal precipitation to less than 90 ± 32 kyr. Overlapping spectra of single zircon crystallisation ages and their trace element distributions from the pre-, syn and post-ore tonalite porphyries reveal protracted zircon crystallisation together with 20 apatite and plagioclase within the same magma reservoir over >300 kyr. The presented petrochronological data constrains a protracted early >200 kyr interval of melt differentiation and cooling within a large heterogeneous magma reservoir leading up to ore formation, followed by magma storage in a highly crystalline state and chemical and thermal stability over several 10s of kyr during which fluid expulsion formed the ore deposit. Irregular trace element systematics suggest magma recharge or underplating during this final short time interval. 25 The comparison of high precision CA-ID-TIMS results with in-situ LA-ICP-MS and SHRIMP U-Pb geochronology data from the same zircon grains allows a comparison of the applicability of each technique as a tool to constrain dates and rates on different geological timescales. All techniques provide accurate dates but with variable different precision. Highly precise dates derived by the calculation of the weighted mean and standard error of the mean of zircon dates obtained by in-situ techniques can lead to ages of unclear geological significance that are older than the maximum ages of emplacement given by 30 the CA-ID-TIMS ages of the youngest zircons in each sample. significantly older suggested emplacement ages than those determined by high-precision CA-ID-TIMS geochronology. This lack in accuracy of the weighted means is due to the protracted nature of zircon crystallisation in upper crustal magma reservoirs, suggesting that standard errors should not be used

We thank the reviewer for the valid point that the reasoning for the interpretation of the youngest U-Pb dates as the porphyry emplacement ages should be made earlier. As pointed out in the manuscript annotated by the reviewer it was previously in lines 578 -579 in the methods section. We have added the reasoning with a bit more detail to section 4.3 "CA-ID-TIMS geochronology". Porphyry intrusions are volumetrically minor sub-volcanic intrusions and are considered to cool rapidly upon emplacement. It is thus assumed that most, if not all, zircons crystallise in the underlying magma reservoir resulting in the extended timescales of zircon crystallisation. Zircon is considered a low temperature phase crystallising until reaching the solidus the youngest recorded zircon and thus records the full crystallisation of the intrusions. The individual uncertainty of a zircon date is sufficient to account for the timescales of porphyry cooling (<10 kyr; e.g. Cathles, 1977).
(2) A somewhat related problem concerns the question of the validity of the results. I am impressed by the high quality of the data, the superb blanks and the high precision. Nevertheless, a central factor in all data sets is the reproducibility of individual analyses. You are measuring 0.5 pg of Pb, next to nothing, and still achieve a very good precision. But is the precision identical with, or less good than the reproducibility of such measurements? To substantiate the solidity of the work, the authors should present information that backs up the implication at the zircon age of each individual zircon grain is reproducible, the alternative being that the larger spread of the ages in each sample may represent a closer measure of the reproducibility. I have seen some very good such data sets in other papers that support their validity, but the question is central with every new application and needs to be addressed.
We thank the reviewer for outlining the high quality of the presented data. Indeed, we are measuring very low quantities of Pb. However, we are convinced that the results are reproducible. The zircon standards referred to and referenced in the manuscript (Aus_Z7_5, von Quadt et al., 2016) contain similarly low amounts of radiogenic Pb (0.5 -4 pg), are of similar age (2.41 Ma) and most importantly are reproducible on the kyr scale.. These were analysed over the same time interval, under the same conditions and in the same lab as the zircons analysed for this study. And these measurements A more indirect assurance that our data is reproducible is that timescales of zircon crystallisation appear to be remarkably similar for studies on porphyry deposits not only conducted in this lab, but also in other labs (Fig. 8). These studies have been conducted on deposits of variable age and thus on zircons with hugely variable radiogenic Pb contents. Finally, the sequence of youngest ages matches the geological emplacement sequence, despite the much larger range of older zircons in each sample; an observation that holds for every single case of several other deposits we studied with this approach. This systematics would be impossible to explain if the age variations were analytical artefacts, and it a also corroborates our interpretation of the youngest zircon in each sample being close to the age of emplacement and magma quenching and termination of zircon crystallization.
(2) My third main point concerns the subsidiary part of the paper, which discussed the comparison of IDTIMS with ICP and SIMS data and reflects on their applications, correctness, and statistical factors. I find this parts absolutely atrocious, and I highly recommend to cut it out. The ICP analyses of these young zircons achieve intensities of maybe 100 cps for mass 206, for measurements lasting less than a minute, and there is no indication that it even gets to evaluate things like the need to correct for common Pb. So, the results are of very low precision, and it is a wonder that they are even close to the real values. The SIMS data are more substantial, but also they face incredible measurement challenges. So, really, all the arguments on statistics and processes cannot get around these basic limitations. And talking about them to such an extent is like watching children playing in the sand. Boring. Suggest cutting this parts out, keeping them for some contribution to a technical workshop, and not use them to spoil an otherwise interesting paper.
We appreciate the reviewer outlining the low precision of the individual LA-ICP-MS dates and SHRIMP dates. We also appreciate the positivity of Reviewer #2 regarding this section. The main point of this section is not that the LA-ICP-MS dates further define the geological interpretation, in which case they could be considered unnecessary. However, we compare the three most commonly applied U-Pb techniques on zircons from the same samples and in the case of TIMS and LA-ICP-MS on the same zircon grains. From this comparison (of a type that has, to our knowledge, not been published before), we can show (1) that the large number of young low precision LA-ICP-MS dates is remarkably accurate as a bulk data-set but that (2) the calculation of the weighted mean and the standard error from LA-ICP-MS populations as currently practiced in the copious literature needs more careful consideration. Using weighted means on such young data-sets as estimates for any geological event or process can result in highly precise dates without any geological significance. We therefore believe that this discussion is of interest to a broad readership. We tried to shorten the section and to focus on our main points and hope that the reviewer and editor can accept the revised section.
1. My main point of discussion involves the use of single "oldest" and "youngest" zircons to constrain the duration of zircon crystallization and metal precipitation. For the particular regime the authors are working in (N _ 15, apparent _t _ 10-20_), the competing effects of undersampling and analytical dispersion likely mostly cancel. On such a basis, the authors could perhaps argue to continue with this approach if they wish. However, "oldest/youngest zircon" is still not inherently statistically robust. One general solution (to which I am obviously biased) would be that of doi:10.7185/geochemlet.1826 (if you go this route, I would probably suggest a uniform ~ fxtal) -but my own work is certainly not the only option here. As I understand it, Pieter Vermeesch also has a perfectly workable analytical minimum age calculator (effectively based on an assumption of a truncated normal ~ fxtal) in IsoplotR. In either case, it will not materially affect the major conclusions of the study.
We thank the reviewer for pointing us towards stochastical sampling approach to determine porphyry emplacement ages. We have calculated emplacement ages based on this approach using the interactive Jupiter notebook on https://github.com/brenhinkeller/BayeZirChron.c. We have addressed the results in the discussion (Section 5.5: lines 619-622) and have added the emplacement ages to the appendix. Indeed, the different treatments of the CA-ID-TIMS result in overlapping results with little variation. More importantly the durations and timescales remain nearly identical. duration of metal precipitation to less than 90 ± 32 kyr. Overlapping spectra of single zircon crystallisation ages and their trace element distributions from the pre-, syn and post-ore tonalite porphyries reveal protracted zircon crystallisation together with 20 apatite and plagioclase within the same magma reservoir over >300 kyr. The presented petrochronological data constrains a protracted early >200 kyr interval of melt differentiation and cooling within a large heterogeneous magma reservoir leading up to ore formation, followed by magma storage in a highly crystalline state and chemical and thermal stability over several 10s of kyr during which fluid expulsion formed the ore deposit. Irregular trace element systematics suggest magma recharge or underplating during this final short time interval. 25 The comparison of high precision CA-ID-TIMS results with in-situ LA-ICP-MS and SHRIMP U-Pb geochronology data from the same zircon grains allows a comparison of the applicability of each technique as a tool to constrain dates and rates on different geological timescales. All techniques provide accurate dates but with variable different precision. Highly precise dates derived by the calculation of the weighted mean and standard error of the mean of zircon dates obtained by in-situ techniques can lead to ages of unclear geological significance that are older than the maximum ages of emplacement given by 30 the CA-ID-TIMS ages of the youngest zircons in each sample. significantly older suggested emplacement ages than those determined by high-precision CA-ID-TIMS geochronology. This lack in accuracy of the weighted means is due to the protracted nature of zircon crystallisation in upper crustal magma reservoirs, suggesting that standard errors should not be used 2 as a mean to describe the uncertainty in those circumstances. We conclude from this and similar published studies that the succession of magma and fluid pulses forming a single porphyry deposit and similarly rapid geological events are too fast to 35 be reliably resolved by in-situ U-Pb geochronology, and that assessing the tempo of ore formation requires ID-TIMS geochronologyThus, geologically rapid events or processes or the tempo of magma evolution are too fast to be reliably resolved by in-situ U-Pb geochronology and require ID-TIMS geochronology.

Introduction 40
Zircon geochronology is widely applied to date geological events and constrain timescales of geological processes. Combined with zircon geochemistry it has improved our understanding of crustal magmatic systems, such as those forming economically important magmatic-hydrothermal porphyry Cu-Au deposits. Advances in analytical techniques resulted in a shift from establishing the ages of magma emplacement or crystallisation to resolving the durations of magmatic and associated hydrothermal processes, such as magma accumulation or recharge, fractional crystallisation or hydrothermal ore formation 45 and it has resulted in unprecedented information about the mechanisms and scales of magma ascent and storage in the Earth's crust (e.g. Vazquez and Reid, 2004;Chamberlain et al., 2014;Barboni et al., 2016;Bucholz et al., 2017).
Porphyry copper deposits provide successively quenched samples of magma extracted from large crustal-scale hydrous magma systems. They are therefore a critical source of information about the processes and rates of magma ascent, magma storage and fluid generation, bridging those of volcanism and pluton formation. The identification of the processes 50 that lead to porphyry deposit formation (e.g. Rohrlach et al., 2005;Audétat et al., 2008;Richards, 2013;Wilkinson, 2013) and the timescales on which they operate can provide us with valuable information about arc magmatic processes but could also potentially help in discriminating possibly fertile magmatic systems from ubiquitous infertile systems resulting in barren intrusions or volcanic eruptions.
Porphyry Cu-Au deposits commonly display clear field relationships of successive generations of porphyritic stocks 55 or dikes, which were injected into subvolcanic and other upper-crustal rock sequences (Sillitoe, 2010). The injected porphyry magmas thus provide snapshots of the underlying, vertically and laterally extensive, magma reservoirs (e.g. Dilles, 1987;Steinberger et al., 2013). Cross-cutting relationships between veins and intrusive rocks suggest temporal overlap of hydrothermal alteration, ore mineralisation and porphyry emplacement (Proffett, 2003;Seedorff and Einaudi, 2004;Redmond and Einaudi, 2010). Strong hydrothermal alteration of the intrusive rocks associated with ore formation severely disturbs the 60 geochemical information of most minerals and whole-rock compositions. While providing important insights into the hydrothermal history of a deposit (e.g. Roedder, 1971;Dilles and Einaudi, 1992;Landtwing et al., 2005;Cathles and Shannon, 2007;Seedorff et al., 2008;Large et al., 2016) it limits the investigation of the magma evolution, especially for the porphyries that are most intimately associated with ore formation. Zircon is a widespread mineral in intermediate to felsic rocks that is 3 unaffected by nearly allis resistant to nearly all hydrothermal alteration and can thus provide unique coherent information 65 about the evolution of a magmatic system.
Geological events and processes that require highest possible precision to be resolved, essentially rely on the accuracy of the chosen analytical technique. Timescales for magmatic and hydrothermal processes involved in porphyry ore formation have been suggested based on in-situ U-Pb data (e.g. Garwin, 2000;Banik et al., 2017;Lee et al., 2017) and increasingly precise 80 CA-ID-TIMS geochronologgeochronology, which became increasingly precise y (e.g. von Quadt et al., 2011;Chelle-Michou et al., 2014;Buret et al., 2016;Tapster et al., 2016;Gilmer et al., 2017;Large et al., 2018). However, several studies applying multiple techniques on to the same sample sets have resulted in differing dates (von Quadt et al., 2011;Chiaradia et al., 2013;Chelle-Michou et al., 2014;Chiaradia et al., 2014;Correa et al., 2016). The discrepancy demands for a more detailed understanding of the precision and accuracy of the techniques and the statistical data treatment that are applied to derive a 85 geological age. This is not only fundamental for resolving dates and rates of geological processes in porphyry ore deposit research but provides more general insights into the geological meaning of equally affects magmatic dates and rates obtained by U-Pb geochronology.
For the present paper, we obtained a large dataset of zircon geochemistry and geochronology by laser ablationinductively coupled plasma-mass spectrometry (LA-ICP-MS) coupled tofollowed by high-precision geochronology of the 90 same zircon fragments/segments/crystals utilising chemical abrasion-isotope dilution-thermal ionization mass spectrometry (CA-ID-TIMS). These coupled data from the world-class Batu Hijau porphyry Cu-Au deposit allows to resolve the chemical evolution and the changing physical state of the magma reservoir over time as well as the timescales of hydrothermal processes.
In addition, previously published data on the same lithologies permit a critical comparison of two in-situ microanalytical methods (SHRIMP data by Garwin (2000), LA-ICPMS presented here) with high-precision U-Pb CA-ID-TIMS 95 geochronology (this study). This allows us to critically compare the effects of variable degrees of precision and of the statistical treatment of data on the resulting interpreted ages and it provides a mean to test the accuracy of the different techniques. The Pliocene, island-arc hosted world-class porphyry deposit of Batu Hijau is located on Sumbawa island, Indonesia (Fig. 1), and it is one of the largest Cu and Au resources in the Southwest Pacific region (7.23 Mt Cu and 572 t Au: Cooke et al., 2005).
It is currently the only mined porphyry deposit in the Banda-Sunda volcanic arc, where Cu-Au porphyries are restricted to a narrow segment of the eastern Sunda-Banda arc from 115°E and 120°E (Fig.1). where Australian plate is being subducted since the Eocene (Hall, 2002). 105 The exposed islands of the Sunda-Banda arc are characterised by Late Oligocene to Early Miocene calc-alkaline basaltic to andesitic arc rocks that are overlain or intruded by a Late Miocene to Pleistocene calc-alkaline volcanic and plutonic rock suite ranging from basaltic to rhyolitic compositions (Hamilton, 1979;Hutchison, 1989). The magmatic arc hosts a variety of ore deposit types, including porphyry-Cu-Au deposits, high-, intermediate-and low-sulphidation epithermal deposits and a VMS-type deposit on Wetar (Fig. 1). 110
The distribution of volcano-sedimentary units, intrusions and the current coastline of Sumbawa are controlled by a major arctransverse, left-lateral oblique-slip fault zone (Arif and Baker, 2004;Garwin et al., 2005). The hypabyssal stocks in the Batu Hijau district are intruded into an Early to Middle Miocene volcano-sedimentary rock sequence (< 21 Ma based on biostratigraphy: Adams, 1984;Berggren et al., 1995) that reaches thicknesses of up to 1500 m in southwestern Sumbawa. The low K2O, calc-alkaline, sub-volcanic intrusive rocks in the Batu Hijau district have andesitic to quartz-dioritic and tonalitic compositions (Foden and Varne, 1980;Garwin, 2000) and were emplaced in several pulses during the Late Miocene and Pliocene (Garwin, 2000). Over this multi-million year magmatic history, a continuous 145 geochemical evolution towards more fractionated lithologies is indicated by whole-rock chemistry and Fe-isotopic evidence of the magmatic rock suite in the Batu Hijau district (Garwin, 2000;Wawryk and Foden, 2017). Within the Batu Hijau deposit, andesite porphyries and different quartz-diorite bodies are the earliest recognized stocks, whereas three tonalite porphyries are the youngest exposed intrusions (Clode, 1999). These tonalite porphyries, which are associated with economically important Cu-Au mineralization and pervasive hydrothermal alteration at Batu Hijau, were emplaced as narrow semi-cylindrical stocks 150 into a broad ENE trending structural dome between ~3.9 -3.7 Ma ( Fig. 2: Garwin, 2000). Based on petrography and crosscutting relationships they were termed Old Tonalite, Intermediate Tonalite and Young Tonalite ( Fig. 3: Meldrum et al., 1994;Clode, 1999;Setynadhaka et al, 2008).
All three tonalite intrusions are petrographically similar and are geochemically described as low-K calc-alkaline tonalites (Idrus et al., 2007). Least altered specimens contain phenocrysts of plagioclase, hornblende, quartz, biotite, magnetite 155 ± ilmenite hosted in an aplitic groundmass of plagioclase and quartz (Fig. 3: Mitchell et al., 1998;Clode, 1999;Garwin, 2000;Idrus et al., 2007). Notably, all three porphyry intrusions lack potassium feldspar. Identified accessory minerals include apatite, zircon and rare titanites. Relicts of clinopyroxene can be identified within the tonalites. Vein density, ore grade and alteration intensity decrease from the Old to Young Tonalite. The Old Tonalite is the volumetrically smallest occurring mostly at the edges of the composite stock. It can clearly be identified in drill-core where its veins are truncated by later intrusions 160 ( Fig. 3) but it is currently not separated from the Intermediate Tonalite by the mine geology department at Batu Hijau, because their phenocryst proportion is almost indistinguishable (Fig. 2). Thus, it is not displayed as a separate unit in Figure 2 but mapped together with the Intermediate Tonalite. It locally contains the highest ore-grades (>1 % Cu and >1 g/t Au) and its matrix is characteristically coarsest of the three tonalite intrusions. The Intermediate Tonalite is the volumetrically largest of the three porphyry intrusions and strongly mineralized (Fig. 2). The Intermediate Tonalite is porphyritic with phenocrysts, 165 including characteristic euhedral quartz phenocrysts, <8 mm in diameter (Fig. 3b). The Young Tonalite is the youngest intrusive rock in the district cutting most vein generations, ore mineralization and alteration (Fig. 3c, e). It is strongly porphyritic with largest observed phenocrysts, including euhedral quartz phenocrysts, and contains elevated but sub-economic metal grades (<0.3 % Cu and <0.5 g/t Au).

phenocrysts <8 mm and is characterized by the a higher abundance in 'quartz eyes'. d) Abundant veins in the equigranular Old tonalite are truncated by the later porphyritic Intermediate tonalite. e) Strongly veined Intermediate tonalite is truncated by the barren and little altered Young tonalite. Dashed-green lines indicate intrusive contacts. f) Representative zircons that display dominant oscillatory zoning and areas with little zoning. Circles indicate domains selected for LA-ICP-MS analyses (30 μm in diameter). 180
Copper and gold are not distributed uniformlysystematically zoned within the deposit. High Au-zones are tightly enveloped around the tonalite stocks whereas high copper grades extend further out into the volcanic lithic breccia and the equigranular quartz diorite (Fig. 2). Lowest Cu/Au ratios occur towards and below the current pit floor and higher Cu/Au ratios are recorded peripheral to the central porphyry stock and towards the upper, already mined part of the ore body. A positive 185 correlation between vein density and Cu and Au contents was described at Batu Hijau (Mitchell et al., 1998;Clode, 1999;Arif and Baker, 2004). A-veins were suggested to comprise ~80 % of all quartz veins and contain a similar fraction of the Cu (Mitchell et al., 1998). Most earlier authors suggested that the bulk of the Cu and Au were precipitated as bornite during early A-vein formation and converted to later chalcopyrite and gold associated with AB and B vein formation (Clode, 1999;Arif and Baker, 2004;Proffett, 2009). Other More recent studies on vein relationships and mineralogy using SEM-CP petrography 190 combined with fluid inclusion analyses suggests that Cu-Au ore mineralization including bornite, chalcopyrite and gold all precipitated with a late quartz generation postdating high-temperature A and AB vein quartz, at lower temperature together with the formation of brittle fractures associated with thin chloritewhite mica halos (~C-veins and 'paint veins'; C-veins (Zwyer, 2011;. Irrespective of the relative debated timing of stockwork quartz veins and economic ore mineral depositionmetal introduction in the Old and Intermediate tonalites, the Young Tonalite cuts through all high-grade Cu 195 and Au zones demonstrating its late, largely post-mineralisation emplacement (Fig. 2, 3e). Therefore, the maximum duration of economic mineralisation is bracketed by the emplacement ages of the Cu-Au-rich Old Tonalite pre-dating it and the Young Tonalite post-dating it. and zircons separated with conventional techniques, including Selfrag TM disintegration, panning and heavy liquid mineral 9 separation (methylene iodide; 3.3 g/cm 3 ). Selected zircons were annealed for 48 hours at 900°C, mounted in epoxy resin and polished to reveal their crystal interior. Polished zircons were carbon coated and imaged using scanning electron microscopy cathodoluminescence (SEM-CL; Tescan EOscan VEGA XLSeries 4 Scanning Electron Microscope) prior to in situ LA-ICP-MS analysis for trace elements and U-Pb isotopes employing a 193 nm ASI Resolution (S155) ArF excimer laser with a 30 210 µm spot diameter, 5Hz repetition rate and 2 J cm -2 energy density coupled to an Element SF-ICP-MS. A detailed description of the method including data reduction can be found in Guillong et al. (2014) and the supplementary material, including results on secondary reference materials. Generally, at least one spot was chosen in the interior (core) and one in the exterior (rim) part of the zircon but up to four individual spots were analysed per zircon (Fig. 3f) to obtain in-situ geochemical information and U-Pb dates. All 206 Pb/ 238 U dates were corrected for initial 230 Th-238 U disequilibrium in the 238 U-206 Pb decay chain (e.g. 215 Schärer, 1984). Ratios of Th/U recorded by zircons cluster around 0.3 -0.6 and the dates were therefore corrected assuming a constant Th/Umelt of 2 based on partition coefficients (0.25) by Rubatto and Hermann (2007). Variation of the assumed Th/Umelt by ±0.5 would result in changes of individual 238 U-206 Pb dates of <10 kyr, far below analytical uncertainty.
Titanium concentrations in zircon have been calibrated as a proxy for the crystallization temperature of zircons (Watson and Harrison, 2005;Watson et al., 2006;Ferry and Watson, 2007) and have been widely used in igneous and ore 220 deposit petrology (e.g. Claiborne et al., 2010b;Reid et al., 2011;Chelle-Michou et al., 2014;Dilles et al., 2015;Buret et al., 2016;Lee et al., 2017). The determination of accurate zircon crystallisation temperatures by Ti-in-zircon thermometry (Ferry and Watson, 2007) requires reliable estimates for the activity of SiO2 and TiO2 (aSiO2 and aTiO2) during zircon crystallization.
Based on previous studies on porphyry deposits we utilize an aSiO2 of 1 and an aTiO2 of 0.7 (Chelle-Michou et al., 2014;Buret et al., 2016;Tapster et al., 2016;Lee et al., 2017;Large et al., 2018) reflecting quartz and titanite saturation (Claiborne et al., 225 2006;Ferry and Watson, 2007). Titanite saturation during zircon crystallization is ambiguous at Batu Hijau (see discussion) but changes in the assumed aTiO2 result in systematic changes of all zircon crystallization temperatures and will therefore not affect the interpretation of relative temperature changes: a change of the aTiO2 by ±0.2 would result in a variation of about ±30°C.
Imaging by CL and followed by low-precision but spatially resolved LA-ICP-MS U-Pb datinges and geochemical 230 data microanalysis by LA-ICP-MS were used to evaluate potential inherited zircon populations and to select inheritanceinclusion-free zircons for subsequent dissolution and analysis by high-precision U-Pb geochronology by CA-ID-TIMS. Selected crystals were removed from the epoxy mount chemically abraded (CA) for 12-15 hours at 180°C using techniques modified from Mattinson (2005). Zircons were spiked with 6-8 µg of the EARTHTIME 202 Pb-205 Pb-233 U-235 U tracer solution (ET2535; Condon et al., 2015;McLean et al., 2015) and dissolved in high-pressure Parr bombs at 210°C for >60 hours. 235 Dissolved samples were dried down and redissolved in 6N HCl at 180°C for 12 hours. Sample dissolution, ion exchange chromatography modified from Krogh (1973) and loading onto zone-refined Re filaments were conducted at ETH Zürich and are described in detail by Large et al. (2018). High-precision U-Pb isotopic data were obtained employing thermal ionization mass spectrometry at ETH Zürich (Thermo Scientific TRITON Plus). Pb was measured sequentially on a dynamic MassCom secondary electron multiplier and U was measured in static mode as U-oxide using Faraday cups fitted with 10 13 Ω resistor 240 amplifiers Wotzlaw et al., 2017). Data reduction and age calculation were performed using the algorithms and software described in McLean et al. (2011) and Bowring et al. (2011). All 206 Pb/ 238 U dates were corrected for initial 230 Th-238 U disequilibrium in the 238 U-206 Pb decay chain (e.g. Schärer, 1984) using a constant Th/U partition coefficient ratio of 0.25 (Rubatto and Hermann, 2007) assuming that variations in Th/U of the zircons result from different Th/U of the crystallising melt and not from variations in relative zircon-melt partitioning of Th and U. High-precision U-Pb dates were 245 obtained from 45 zircons, all of which were previously analysed by LA-ICPMS.

Optical zircon appearance and SEM-CL petrography
Zircons were extracted from the three tonalites (Old, Intermediate and Young Tonalite) and the equigranular quartz diorite. 250 Zircon crystals from all three tonalite samples are colourless, euhedral to subhedral and variable in size with c-axis lengths of 100 -500 µm and aspect ratios between 1:2 and 1:4 (Fig. 3f). Thin section observations reveal zircons that are enclosed by phenocrysts and those thatalso occur within the fine-grained groundmass suggesting protracted zircon crystallisation within the magma until emplacement of the tonalite porphyries. Investigation of mineral separates and mounts with a binocular microscope reveals that many zircons contain small (<<20 µm) mineral or melt inclusions. SEM-CL imaging reveals few 255 unzoned and sector zoned zircon domains, but most zircons exhibit oscillatory zoning (Fig. 3f).
Only few broken zircon fragments could be identified from heavy mineral separates of the equigranular quartz diorite, but these indicate originally euhedral to subhedral shapes. Five of these broken grains, typically <200 µm long with aspect ratios of ~1:4, could be identified and were mounted. Four zircons were unzoned and one was oscillatory zoned.
However, some core-rim trends, especially, from the Young Tonalite display increasing Th/U and decreasing Yb/Dy ratios In most zircons, Ti-concentrations decrease from core to rim (Fig. 4d, f). This decrease correlates well with increasing Hf and decreasing Th/U. Maximum and minimum values Ti contents for all intrusions are ~10 ppm and ~2 ppm resulting in model crystallization temperatures of 770°C to 650°C (see methods for details). The majority of zircons from the Batu Hijau 290 deposit contain lower U concentrations (<75 ppm) compared to zircons from most other porphyry deposits (several 100 ppm) but individual zircons can contain up to 300 ppm (Fig. 4c). The zircons with high U-concentration do not correspond to the lower Th/U zircons but also contain high Th-concentrations and cover the whole spectra of Th/U ratios observed at Batu Hijau ( Fig. 4c). The Eu-anomaly (Eu/Eu*, which is a mean to quantify the negative inflexure of the normalised REE diagram) increases (Eu/Eu* decrease) with increasing Hf concentrations (Fig. 4e). Zircon analyses from the equigranular quartz diorite 295 plot towards the lowest Hf, Yb/Dy, Yb/Nd and, Eu/Eu* but highest Th/U and Ti end of the trends displayed by the all tonalite zircons (Fig. 4).
Probability density functions (Vermeesch, 2012) are used to test for statistically significant differences between the overlapping zircon populations of the different tonalites and between core and rim analyses from the same tonalite porphyries ( Fig. 4f, g, h). The Hf and Ti concentrations as well as the europium Eu-anomaly of zircons display overlapping distributions 300 for the Intermediate and Young tonalites. The Old Tonalite zircon population peaks at higher Ti concentrations and Eu/Eu* as well as lower Hf concentrations than the younger tonalites. Core and rim analyses from zircons of the Old Tonalite document decreasing Ti and Eu/Eu* together with increasing Hf concentrations from cores to rims. Hafnium contents of the rim analyses peak at higher concentrations than the core analyses within the Intermediate and Young Tonalite with thewhereas Eu/Eu* displaysing the opposite effect. Populations illustrating titanium concentrations of the two younger tonalites however, display 305 no systematic changes between core and rim.

CA-ID-TIMS geochronology
We dated 16 zircons each of the Old and Intermediate Tonalite and 13 zircons of the Young Tonalite by high-precision CA-310 ID-TIMS geochronology. The youngest zircon eachs of the Old, Intermediate and Young Tonalite yield 230 Th -238 U disequilibrium corrected 206 Pb/ 238 U zircon dates of 3.736 ± 0.023 Ma, 3.697 ± 0.018 Ma and 3.646 ± 0.022 Ma (individual grain ±2 Fig. 5). We interpret these dates as the time of respective porphyry emplacement based on the assumption that zircons grew at depth up to the point that the magma cooled rapidly upon injection into the subvolcanic environment (cf. Oberli et al., 2004;Schaltegger et al., 2009;von Quadt et al., 2011;Samperton et al., 2015;Large et al., 2018) (c.f. Oberli et al., 2004;von 315 Quadt et al., 2011;Samperton et al., 2015;Large et al., 2018)) . Reproducibility of the individual dates is corroborated by reproducible dates for all analysed CA-ID-TIMS standards analysed during over the time of analyses of the presented samples.
Standards include the Aus_Z7_5 (von Quadt et al., 2016) that contains similarly low amounts of radiogenic Pb (0.5 -4 pg) and is of Pliocene age Despite the small differences in emplacement age, the age sequence is consistent with field observations documenting the 320 emplacement sequence (Fig. 3). consistent with field observations (Fig. 3). The time intervals between emplacement of the Old and Intermediate Tonalite and between the Intermediate and Young Tonalite can therefore be constrained to 39 ± 29 ka and 51 ± 28 ka, respectively. The Recorded minimum duration of zircon crystallization, as defined recorded by the oldest and youngest zircon of each sample, spreads over 246 ± 28 kyr, 212 ± 32 kyr and 171 ± 26 kyr for the Old, Intermediate and Young Tonalite (Fig. 5). The overall duration of recorded zircon crystallization is 336 ± 27 ka. Using the youngest zircon population, 325 rather than the youngest individual zircon as the best approximation for porphyry emplacement (c.f. Samperton et al., 2015;Buret et al., 2016;Tapster et al., 2016) would result in slightly older emplacement ages (~20 kyr) but nearly identical durations of zircon crystallisation and time intervals between porphyry emplacement events (see Supplementary Material).
Our high-precision CA-ID-TIMS dates precisely constrain protracted zircon crystallization over several 100 ka and successive emplacement of the three porphyritic tonalite bodies at Batu Hijau within 90 ± 32 ka. 330 Ratios of Th/U obtained by CA-ID-TIMS analyses on the same sample volume illustrate no systematic variation with time. Values vary inconsistently between 0.4 and 0.6 over the whole recorded time interval (Fig. 6).

In-situ U-Pb geochronology 345
Trace element and U-Pb isotopic data were obtained for each LA-ICP-MS spot (Fig. 7) prior to CA-IC-TIMS dating. Low Uranium concentrations and the young ages of the analysed zircons resulted in high individual uncertainties for individual in-14 situ U-Pb dates (Mean: 10%; Minimum: 3%; Maximum: 41%). All individual spot analyses of the three tonalites that were not discarded due to common Pb or strong discordance yield Pliocene dates (2.98 ± 1.06 -4.95 ± 0.54 Ma: Fig. 7) with no apparently inherited zircons. All in-situ dates of individual samples illustrate continuous arrays and do not indicate more than 350 one population of zircons per sample (Fig. 7). Weighted means of all zircon analyses from each tonalite are 3.879 ± 0.027, 0.065, 0.32 (n = 207, MSWD = 2.1), 3.778 ± 0.023, 0.061 , 0.62 (n = 189, MSWD = 2.5) and 3.751 ± 0.023, 0.060, 0.29 Ma (n = 158, MSWD = 2.6) from oldest to youngest (Fig. 7), where the stated uncertainties are the standard error of the weighted mean, the standard error including an external uncertainty of 1.5 % as suggested by Horstwood et al. (2016)
Similar to the LA-ICP-MS analyses in this study, individual uncertainties of the dates were elevated (0.12 -0.30 Ma: ~5 -10 % uncertainty) due to low U concentrations and the young zircon crystallisation ages. As all dates of each sample statistically formed a single populationsappear to represent the same populations (Supplementary Material) weighted means were calculated from of all zircons of a sample, these were interpreted as the intrusion ages of the tonalites by Garwin (2000). The 370 reported zircon dates were not corrected for 230 Th-238 U disequilibrium. For comparability we will only consider zircon dates that are corrected for initial Th/U disequilibrium (Schärer, 1984:

Timing and duration of magmatic and hydrothermal processes leading to porphyry Cu formation
The three tonalite intrusions each record protracted zircon crystallisation over ~200 kyr, as resolved by high-precision ID-TIMS geochronology. The older zircon dates from the Young and Intermediate tonalites overlap with the younger zircons of the older intrusion/s (Fig. 5). This overlap together with the consistent trace element systematics of the three samples (Fig. 4) strongly suggests crystallisation of all zircons within the same magma reservoir. the largely overlapping trace element 395 systematics recorded by zircons are here used to infer zircon crystallisation within the same mid-to upper crustal magma reservoir that sourced magmas forming the three tonalitic porphyry stocks but most likely also volatiles and metals to form the porphyry Cu-Au deposit. High-precision geochronology records a total duration of zircon crystallisation of 336 ± 27 kyr, which is also a minimum estimate for the lifetime of the deeper reservoir underlying Batu Hijau. The first exposed and highly mineralised tonalite intrusion (Old Tonalite) was injected into the upper crust 246 ± 28 kyr after the onset of zircon 400 crystallization. Emplacement of the three tonalites occurred within 90 ± 32 kyr. Emplacement of the Old Tonalite was followed by the emplacement of the Intermediate Tonalite after 39 ± 29 kyr and the Young Tonalite was emplaced after a further 51 ± 28 kyr.
The maximum duration of ore formation is defined by the timespan between the emplacement of the pre-to synmineralisation Old Tonalite and the post-mineralisation Young Tonalite (Fig. 3d, e) and can be therefore constrained to less 405 than 122 kyr. This maximum duration is in good agreement with previous geochronological studies indicating timescales of ore formation from <100 kyr to <29 kyr (Fig.8, 9: von Quadt et al., 2011;Buret et al., 2016;Tapster et al., 2016). It is also coherent with results from thermal modelling studies (Cathles, 1977;Weis et al., 2012) and modelling of diffusive fluid-rock equilibration (Cathles and Shannon, 2007;Mercer et al., 2015;Cernuschi et al., 2018) suggesting timescales of ore formation between a few ka and 100 kyr. Strongly elevated Cu-and Au-grades in the Old Tonalite and somewhat lower, but still 410 economic, grades within the Intermediate Tonalite (Clode, 1999;Garwin, 2000;Arif and Baker, 2004) together with crosscutting relationships (Fig. 3d, e) indicate that mineralisation occurred within at least two but possibly more pulses: (i) one strong mineralisation pulse associated with or slightly postdating the emplacement of the Old Tonalite but predating the injection of the Intermediate Tonalite (Fig. 3d); (ii) a second pulse is bracketed by the intrusion of the Intermediate and the Young Tonalite (Fig. 3e). More than one episode of mineralisation is also inferred based on detailed mineralogy and vein 415 petrography (see Geology section: Arif and Baker, 2004;Zwyer, 2011). This further strengthens the hypothesis that individual ore-forming hydrothermal pulses are relatively short events, possibly on the millennial or sub-millennial scale (Cathles, 1977;Weis et al., 2012;Mercer et al., 2015), but that the formation of large economic Cu-Au deposits occurs in several pulses occurring over a few 10s of kyr but ≤100 kyr (von Quadt et al., 2011;Weis et al., 2012;Cernuschi et al., 2018). 420

Reconstructing the chemical and physical evolution of a porphyry-forming magma reservoir
Trace element systematics of zircons are powerful geochemical proxies, if applied correctly, as they record the magma evolution and characterise the magmatic system, that they crystallised from (e.g. Hoskin and Schaltegger, 2003;Reid et al., 2011;Schoene et al., 2012;Wotzlaw et al., 2013;Chamberlain et al., 2014;Samperton et al., 2015). The largely overlapping trace element systematics recorded by zircons together with the protracted nature of zircon crystallisation are here used to infer 425 zircon crystallisation within the same mid-to upper crustal magma reservoir that sourced magmas forming the three tonalitic porphyry stocks but most likely also volatiles and metals to form the porphyry Cu-Au deposit. At Batu Hijau we are able to reconstruct the magmatic evolution over 336 ± 27 kyr of recorded zircon crystallization.
Ratios of Th/U ratios and Hf concentrations are commonly used as proxies for the degree of crystal fractionation within a magma reservoir (e.g. Claiborne et al., 2006;Claiborne et al., 2010b;Samperton et al., 2015). The systematically 430 decreasing Th/U ratios and increasing Hf concentrations between samples and from cores to rims (Fig. 4) are indicative of progressive melt differentiation during zircon crystallisation. The good correlation of these melt evolution proxies with decreasing Ti-contents (Fig. 4) further suggests progressive cooling during differentiation. Ratios of HREE over MREE or LREE (e.g. Yb/Dy, Yb/Nd) can be utilised to make inferences about the co-crystallising mineral assemblage. Titanite for example preferentially depletes the melt in MREE resulting in distinct trace element patterns recorded by co-crystallizing 435 zircon (e.g. Reid et al., 2011;Wotzlaw et al., 2013;Samperton et al., 2015;Loader et al., 2017). The systematically higher HREE (e.g. Yb) over MREE (e.g. Dy) and LREE (e.g. Nd) contents in the rims of most zircons relative to their cores (Fig. 4a) thus indicate zircon crystallisation from a fractionally crystallising magma with co-crystallisation of minerals that preferentially incorporate MREE and LREE (e.g. apatite, titanite, amphibole). At Batu Hijau apatites were petrographically identified, whereas magmatic titanite occurs very subordinately. The apparent lack of magmatic titanite is unusual as it is reported as a 440 common accessory phase in many other porphyry-Cu deposits (e.g. Bajo de la Alumbrera, El Salvador, Ok Tedi, Oyu Tolgoi).
The absence of euhedral titanite within the mineral separates could be the result of dissolution during intense hydrothermal alteration (van Dongen et al., 2010). The decrease of Eu/Eu* correlating with proxies of increased fractionation (Hf, Fig. 4e) and during zircon growth (Fig. 4f) suggests co-crystallisation of plagioclase and could indicate a lack of titanite crystallisation, or subordinate crystallisation, as already minor titanite crystallisation strongly increases the Eu/Eu* recorded by zircon (Loader 445 et al., 2017). This apparent lack of titanite crystallisation identify apatite as the main REE fractionating mineral during zircon crystallization.
Trace element compositions of zircons from the equigranular quartz diorite suggest crystallisation within a hotter and less evolved magma than the zircons from the tonalites (Fig. 4). In principle, this might indicate that all zircons analysed in this study have crystallised from the same reservoir, where the zircons from the equigranular quartz diorite reflect the earliest 450 crystallised zircons from least evolved melt. However, the >2 Ma time gap is longer than the thermal lifetime of any recognised upper-crustal magmatic body (e.g. Schoene et al., 2012;Wotzlaw et al., 2013;Caricchi et al., 2014;Samperton et al., 2015;Eddy et al., 2016;Karakas et al., 2017) and longer than considered possible based on thermal modelling (Jaeger, 1957;Annen, 2009;Barboni et al., 2015). We therefore consider the zircons within the equigranular Diorite to be part of a separate crustal magmatic system not directly related to the ore-forming system that sourced the three tonalitic intrusions. 455 Trace element populations of zircons from the three tonalites demonstrate that the crystallising magma at the time of emplacement of the Old Tonalite was hotter and less fractionated (Fig. 4) than at the time of emplacement of the younger Intermediate and Young Tonalite (i.e. 39 ± 29 ka and 90 ± 32 ka after emplacement of the Old Tonalite, respectively). The good correlation of proxies indicating progressive differentiation (Th/U and Hf) with decreasing Ti concentrations (Fig. 4d) indicates that the magma reservoir cooled during concurrent crystallisation and melt evolution. In-situ analyses of cores and 460 rims are evidence for an evolving magma reservoir over the course of individual zircon crystallisation (decreasing Hf: Fig.   4h). Core-rim systematics of zircons from the Old Tonalite further demonstrate cooling during protracted zircon growth (Fig.   4f). Rarely recorded coherent zircon trace element systematics recording melt differentiation over time are commonly inferred to result from zircon crystallisation within a homogeneous magma that evolved continuouslybest resembles near-closed-system behaviour (e.g. Wotzlaw et al., 2013;Large et al., 2018). The lack of such systematic temporal changes in the chemistry of the 465 zircons ( Fig. 6) indicates that the magma reservoir at Batu Hijau was not evolving homogenously. This could be explained by incremental recharge or assembly of the magma reservoir. However, this would imply at least partial resetting of the intragrain systematics recorded in zircons from the Old Tonalite Large et al., 2018). To explain the intra-grain and inter-sample systematics but absence of temporal trends (Fig. 4, 6), we favour different degrees of crystallinity in the magma reservoir. Overall the reservoir is generally hotter and less evolved at the time of emplacement of the Old Tonalite than 470 thereafter (Fig. 4). We therefore suggest that the magma reservoir underlying Batu Hijau progressively but heterogeneously cooled and crystallised over at least 246 ± 28 ka with potential incremental recharges until emplacement of the Old Tonalite.
A change from a differentiating, crystallising and cooling magma reservoir to a state of chemical and thermal stability is recorded between emplacement of the Old and Young Tonalite (separated by 90 ± 32 kyr) as demonstrated by the trace element systematics of the Intermediate and Young Tonalite porphyries. The indistinguishable highly fractionated and low 475 temperature zircon characteristics (Fig. 4) indicate that the magma reservoir remained in near steady-state conditions between emplacement of the Old and Young Tonalite as coherent intra-grain systematics are not pronounced (Hf) or absent (Ti) in zircons from the younger tonalites (Fig. 4f, h). Irregular zircon trace element systematics in other intrusive magmatic settings have been associated with crystallisation in non-homogenised and small melt batches sometimes with contemporaneous incremental magma addition to 480 the mushy magma reservoir (e.g. Schoene et al., 2012;Buret et al., 2016;Tapster et al., 2016). Geochemically similar zircon chemistries of the Intermediate and Young Tonalite could also result from chemical stability as the magma reservoir reached the 'petrological trap' at a crystallinity of ~55 -65% (Caricchi and Blundy, 2015) where the crystal fraction does not change over a broad temperature interval. Rim analyses that plot outside the mineral co-crystallisation trends than the respective core analyses (Fig. 4) could suggest late-stage crystallisation within a nearly solidified magma that can be characterized by 485 unsystematically variable trace element systematics Lee et al., 2017). Alternatively, they could indicate 20 thermal and possibly chemical rejuvenation of the magma . The latter would help explaining the recorded thermal stability over several 10s of kyr. It is not possible to unambiguously identify one of the two mechanisms as dominant and a concurrence of both is feasible. We therefore propose that in between emplacement of the Old and Young Tonalite the underlying magma reservoir was in a thermally and chemically stable and crystal-rich state and was most likely affected by 490 incremental magma recharge or underplating.
Our data of a porphyry-Cu fertile magmatic system constrain a heterogeneous magma reservoir that was initially dominated by cooling and melt differentiation and evolved into a thermally and chemically stable, crystal-rich magma that possibly experienced incremental recharge. The likely transitional change of reservoir behaviour can be temporally constrained to have occurred between emplacement of the Old and Young tonalites and coincides with the formation of a world-class Cu-495 Au reserve. This suggests that porphyry Cu-Au deposits form after a few 100 ka of cooling and crystallisation, potentially within an originally melt-rich magma reservoir.

Different timescales of processes related to porphyry Cu-Au ore-formation
To date no clear relationship between the duration of magmatic-hydrothermal activity and the size of porphyry deposits can be identified from studies applying high-precision CA-ID-TIMS geochronology. Comparison of published datasets (Buret et 500 al., 2016;Tapster et al., 2016;Large et al., 2018) reveals maximum durations of metal forming events between a few 10 4 to 10 5 yr (Fig. 9). Although these studies are so far constrained to deposits of <10 Mt contained Cu they range over at least one order of magnitude in size (Koloula vs. Batu Hijau). A correlation between the duration of the mineralizing/magmatic event and the total mass of deposited copper had been previously suggested based on compilations of different geochronological data-sets (Chelle-Michou et al., 2017;Chiaradia and Caricchi, 2017;Chelle-Michou and Schaltegger, 2018;Chiaradia, 2020). High 505 durations of ore formation (>1 Ma) were suggested based on Re-Os geochronology on Molybdenite at the giant porphyry deposits and deposit clusters in Chile (>50 Gt Cu: El Teniente, Cannell et al. (2005) and Maksaev et al. (2004); Rio Blanco, Deckart et al. (2012); and Chuquicamata, Barra et al. (2013)). Copper (-gold) mineralising timescales were calculated by subtracting the youngest from the oldest Re-Os date. However, recent Re-Os dates from El Teniente (Spencer et al., 2015) indicate that the spread in dates is more consistent with several short (≤200 kyr) hydrothermal events separated by hiatuses of 510 ~500 kyr. Thus, the large tonnage of these deposits could be the result of the superimposition of several ore forming mid-to upper crustal magmatic systems. As the correlation of deposit size and timescales of shallow magmatic-hydrothermal systems is currently ambiguous we would argue that other variables could be the dominant factors controlling the deposit size, such as magma reservoir size, magma or fluid chemistry, fluid release and focussing mechanisms or the metal precipitation efficiency.
Zircon crystallisation over ~200 kyr before the onset of porphyry-ore formation recorded at Batu Hijau is consistent 515 with other high-precision geochronological studies on porphyry deposits (Fig. 8, 9: Buret et al., 2016;Tapster et al., 2016;Large et al., 2018). The lack of variation observed in these deposits suggests the necessity of a long-lived and continuously crystallising magma reservoir preceding economic ore formation. The recorded ~200 kyr of protracted zircon crystallisation could indicate a period of volatile enrichment as a result of fractional crystallisation and cooling of the magma reservoir before porphyry emplacement. 520 The geochronological data from the Batu Hijau district are further evidence that rapid porphyry emplacement and ore 530 formation (<100 ka) are the product of a longer term evolution (a few 100 ka) of a large magma reservoir underlying the porphyry deposit that is the main driver of ore formation (von Quadt et al., 2011;Chelle-Michou et al., 2014;Buret et al., 2016;Tapster et al., 2016;Buret et al., 2017;Large et al., 2018). Magma reservoirs capable of forming porphyry deposits are in turn part of a longer-term (several Myr) evolution of lithosphere-scale magma systems (Sasso, 1998;Rohrlach et al., 2005;Longo et al., 2010;Rezeau et al., 2016), which is consistent with the >>2 Myr record of intrusive rocks preceding 535 porphyry emplacement and ore formation recorded in the Batu Hijau district (Garwin, 2000;Wawryk and Foden, 2017).

2005). Diagrams are aligned that the onset of zircon crystallisation overlaps in all deposits. Grey bars indicate recorded duration of zircon crystallisation. Yellow bars illustrate maximum durations of total ore formation or individual ore formation pulses. Yellow bar fading out downwards indicates the absence of a 545
post-ore intrusion and the inability to constrain total duration of ore formation. Note that we excluded the sample X176 from Koloula as it is not related to magmatic history leading to ore formation (Tapster et al., 2016).

Resolving lower crustal magmatic processes from Zircon zircon petrochronology
The lack of inheritance within the zircon record at Batu Hijau suggests that the crustal magmas experienced very minor crustal 550 assimilation. Typically, magmas that are associated with porphyry ore formation contain diverse suites of inherited zircons (e.g. Tapster et al., 2016;Lee et al., 2017;Large et al., 2018), which have been interpreted to represent extended interaction with arc lithologies (Miller et al., 2007). This apparent lack of crustal contamination is consistent with the juvenile isotopic signatures (Pb-Pb, Sm-Nd, Rb-Sr) of intrusions in the Batu Hijau district (Garwin, 2000;Fiorentini and Garwin, 2010). The juvenile and "porphyry-fertile" magmas at Batu Hijau have been explained by asthenospheric mantle upwelling through a tear 555 in the subducting slab that resulted from the collision with the Roo rise (Garwin, 2000;Fiorentini and Garwin, 2010). This would also explain why the only mined porphyry-deposit in the Sunda-Banda arc (Batu Hijau) and the most promising prospects (Elang and Tumpangpitu) are located above the inferred margin of the subducting Roo rise (Fig. 1).
The formation of porphyry Cu(-Au) deposits has been commonly associated with the fractionation of amphibole ± garnet in thickened crust (e.g. Rohrlach et al., 2005;Lee and Tang, 2020) within lower crustal magma reservoirs that are active 560 over several Myr (Rohrlach et al., 2005). Zircons have been suggested to directly track this extended lower crustal history (Rohrlach et al., 2005). At Batu Hijau no zircon was identified that crystallised resolvably before the main crystallisation period, which we consider to have occurred in the mid-to upper crust (Fig. 5, and discussion above). Unzoned cores surrounded by oscillatory zoned rims (Fig. 3f) could be interpreted to reflect a two-stage crystallisation process however, the depth of these two processes cannot be resolved and they would have occurred within the few 100 kyr of recorded zircon crystallisation 565 (Fig. 5). As most crystals within a mount are not polished exactly to their centre, the unzoned cores could equally likely represent a polishing effect where the surface of one zone appears as an unzoned core. Therefore, it is highly speculative to directly relate zircon textures to a locus or style of zircon crystallisation.
In the case of Batu Hijau, petrochronology petrochronological data was used to reconstruct the mid-to upper crustal magma evolution but the data can only provide indirect information about the lower crustal processes involved in the formation 570 of the deposit. For example, the overall elevated Eu/Eu* of the investigated zircons (0.4 -0.7; cf. Loader et al., 2017) could be the result of amphibole fractionation in the lower crust, which would have, relatively, enriched the residual melt Eu compared to the other REE. This would be analogous to elevated whole-rock Sr/Y ratios in exposed rocks being indicative of the lower crustal fractionating assemblage (Rohrlach et al., 2005;Chiaradia, 2015). The intra-crystal and intra-sample trends of decreasing Eu/Eu* discussed above describe the evolution within the mid-to upper crustal magma reservoir that was 575 dominated by plagioclase crystallisation and do not reflect any lower crustal process. Zircon can thus directly record the midto upper crustal magma evolution but the information about lower crustal processes is limited to potentially identifying the chemistry of melt and magma that was injected from below into the mid-to upper crust, where zircon started crystallising.

An assessment of the accuracy and precision of CA-ID-TIMS and in-situ U-Pb zircon geochronology
The obtained U-Pb dataset from Batu Hijau, allows a critical comparison of the two zircon U-Pb geochronology techniques 580 (LA-ICP-MS, CA-ID-TIMS) that have different analytical precision and can analyse samples on varying spatial scales.
Previous investigation of the same lithologies by SHRIMP (Garwin, 2000) allows further comparison. The spatially resolved and fast in-situ U-Pb geochronology techniques (LA-ICP-MS or SIMS/SHRIMP) allow the investigation of different crystal domains, whereas the much more time-consuming CA-ID-TIMS analysis of zircons or zircon fragments provides the highest analytical precision. The in-situ techniques can discriminate between different zircon populations within single crystals (e.g., 585 inheritance), whereas CA-ID-TIMS geochronology allows for an >10-fold better analytical precision for individual grains that is required to resolve rapid geochronological events. To increase precision of the in-situ techniques large numbers of individual dates that are considered to represent the same geological event are commonly used to calculate a weighted mean date and standard error of the mean (Wendt and Carl, 1991). On the other hand, the CA-ID-TIMS community has started to measure only small zircon fragments to increase spatial resolution (e.g. Samperton et al., 2015;Smith et al., 2019)). Here, the comparison 590 of the different U-Pb zircon techniques applied to the same rock suite allows an assessment of the accuracy of the techniques and of the effect of statistical treatment on the accuracy and precision of the different techniques.
At Batu Hijau, the youngest individual CA-ID-TIMS U-Pb date of each sample is used as the our best estimateapproximation for the emplacement age of the respective porphyry based on the low number of analyses and high ratio 24 of crystallisation duration to individual uncertainty (Keller et al., 2018). This is based on the assumption that the magma cooled 595 rapidly upon injection into the subvolcanic environment (cf. Schaltegger et al., 2009;von Quadt et al., 2011;Samperton et al., 2015;Large et al., 2018). The resulting porphyry emplacement ages are 3.736 ± 0.023 Ma, 3.697 ± 0.018 Ma, 3.646 ± 0.022 Ma for the Old, Intermediate and Young Tonalite, respectively (Fig. 5). Other statistical means to determine the emplacement ages would be the calculation of a weighted mean for the youngest zircon population (e.g. Buret et al., 2016) or a stochastical sampling approach (Keller et al., 2018). We calculated each alternative and found that the emplacement ages overlap within 600 uncertainty so that the timescales and conclusions derived from this study remain identical (see appendix). The extended range of concordant zircon dates obtained by CA-ID-TIMS does not allow to distinguish between different stages of zircon crystallisation within each sample (e.g., inherited vs. autocrystic) but the common geochemical trends indicate support crystallisation within the sameone common magma reservoir (see above). Thus, the range in zircon dates preceding this emplacement age is interpreted to represent zircon crystallisation within the underlying source magma reservoir over parts or, 605 depending on the timing of onset of zircon saturation, the entirety of its lifetime. The total recorded duration of zircon crystallisation is 336 ± 27 kyr.
Similar toEven more so than the CA-ID-TIMS dates, in-situ analyses by LA-ICP-MS illustrate an extended range of zircon dates that cannot be separated into different stages of zircon crystallisation. However, the span in zircon dates is about a magnitude higher for the in-situ analyses (1.41 ± 0.5 -2.1 ± 1.1 Myr) than obtained by CA-ID-TIMS (0.171 ± 0.026 -0.246 610 ± 0.028 Myr). Such LA-ICP-MS data in isolation might be argued to This could indicate that the LA-ICP-MS data records an extended period of zircon crystallisation not covered by CA-ID-TIMS data, potentially due to sampling bias or by one sampleset being inaccurate, that one data-set is inaccurate or but we suggest (see section 5.6 below) that the span within the in-situ data is the result of analytical scatter and potentially minor amounts of Pb loss or common Pb.
Sampling bias in the selection of the zircons for CA-ID-TIMS geochronology can be excluded as the analyses were 615 conducted on chemically abraded zircons (Mattinson, 2005) that cover the oldest and youngest dates obtained by LA-ICP-MS ( Fig. 10). High accuracy of both, the CA-ID-TIMS and LA-ICP-MS, data-sets are suggested by routine measurements of secondary standards during the LA-ICP-MS analytical run (See Supplementary Material) and regular measurements of zircon standards by CA-ID-TIMS over the period of data acquisition including the Pleistocene Aus_Z7_5 Wotzlaw et al., 2017). The distributions of the zircon dates of each sample, as illustrated by probability density plots 620 ( Fig. 11), illustrate that the peak of the LA-ICP-MS and SHRIMP dates falls within the mean of zircon crystallisation as defined by the CA-ID-TIMS data-set. This suggests that all datasets are accurate but that the in-situ data displays more scatter and lower precision. LA-ICP-MS analyses record younger zircon dates for core analyses than rim analyses in 17 of 49 47 cases, however the LA-ICP-MS dates for core and rimare always overlapping within uncertainty. Direct comparison of U-Pb dates from the same zircon crystals by the two techniques (Fig. 10) reveals that the less-precise LA-ICP-MS data are not 625 correlated with the more precise TIMS ages, and the suggested dates from the two techniques do not overlap within uncertainty in some cases (6/49 47 for rim analyses: Fig. 10B). This could indicate that uncertainties associated calculated for with the LA-ICP-MS data have been underestimated in relation to the achieved precision of the technique. However, due to the high 25 number of analyses it is more likely that it is purely an effect of analytical scatter where 5% of the data do not fall within the 95% confidence interval. This is corroborated by ~7 % (39/554) of LA-ICP-MS dates not overlapping with the minimum 630 overall duration of zircon crystallisation identified by CA-ID-TIMS dates from all porphyries (336 ± 27 kyr). Additionally, minor amounts of Pb loss or common Pb not identified during data-screening could account for some older and younger outliers but the overlapping peaks of the in-situ populations and the mean of CA-ID-TIMS dates support no systematic bias of the bulk-population to younger or older dates. It is therefore concluded that all three techniques are accurate and represent the ~300 -350 kyr of zircon crystallisation. The high number of analyses obtained by LA-ICP-MS together with the lower 635 precision results in extreme outliers that extend the apparent duration of zircon crystallisation but can be regarded purely as an statistical sampling result that does not indicate a more extended duration of zircon crystallization. Therefore, we consider alternative methods of estimating age uncertainties in the following section.analytical artefact.

Determining geological ages, uncertainties and rates from in-situ U-Pb data 650
Understanding the timing of magma emplacement, crystallisation or eruption is essential for determining dates and rates of magmatic processes and those directly related or bracketed by them. Where high-precision CA-ID-TIMS data is not available porphyry emplacement ages are commonly inferred by calculating a weighted mean and standard error from the youngest overlapping population of in-situ U-Pb dates (e.g. Correa et al., 2016;Rezeau et al., 2016;Lee et al., 2017). In the case of Batu Hijau the such a calculation would include all LA-ICP-MS zircon dates for each sample as there is no apparent reason to 655 exclude parts of the data set due to inheritance, common Pb or Pb loss within the datasets (Fig. 7). The resulting weighted mean dates for the Old, Intermediate and Young Tonalite are 3.879 ± 0.027/0.064 (MSWD = 2.1, n = 207), 3.783 ± 0.023/0.061 (MSWD = 2.5, n = 189 ), 3.751 ± 0.023/0.060 (MSWD = 2.6, n = 158) where the first stated uncertainty is the standard error including internal uncertainties and those associated with tracer calibration (Schoene, 2014) and the second includes the added 1.5% external uncertainty as suggested by Horstwood et al. (2016) to account for excess variance. The MSWD for each data-660 set (2.1 -2.6) is elevated in respect to the sample size (n=150-200) based on the formulation by (n=150-200;Wendt and Carl, (1991). This suggests eithering an underestimation of the individual uncertainties or that the data do not represent a normal distribution, e.g. by prolonged zircon crystallisation. However, there is no obvious treatment of the data to obtain more appropriate MSWDs. Under these conditions weighted means and standard errors should not be considered geologically meaningful according to calculated (Wendt and Carl, 1991) but we will nevertheless ignore this here, as is commonly done in 665 the scientific literature, and will usecalculate these numbers to illustrate a few points below. Analogous, the weighted mean and standard error of all zircons analysed by SHRIMP from each sample results in weighted means of 3.74 ± 0.14 Ma (MSWD = 1.2, n = 8), 3.843 ± 0.094 (MSWD = 1.2, n = 18) Ma and 3.81 ± 0.2 Ma (MSWD = 2.35, n = 7) for the Old, Intermediate and Young tonalite, respectively (Fig. 11). The weighted means of the different tonalites obtained by LA-ICP-MS would be in accordance with cross-cutting relationships, whereas the SHRIMP dates overlap within uncertainty. The calculated standard 670 errors for the LA-ICP-MS dates are significantly smaller than for the SHRIMP data. The decrease in the standard errors is directly correlated with the increasing sample size (Wendt and Carl, 1991;McLean et al., 2011b) implying that a comparably high number of SHRIMP analyses would result in similarly low standard errors. Irrespective of the different standard errors the calculated weighted means by SHRIMP and LA-ICP-MS are overlapping within uncertainty, thus seemingly suggesting that both are accurate or similarly inaccurate (see below). 675 At Batu Hijau, emplacement ages determined by CA-ID-TIMS geochronology are systematically younger than the weighted mean dates calculated from in-situ data (100 -150 kyr: except CA-ID-TIMS and SHRIMP for the Old Tonalite) and the emplacement ages determined by CA-ID-TIMS do not overlap with the LA-ICP-MS values mean ages within their attributed uncertainties (Fig. 11). Indeed, disparities between different U-Pb data-sets on the same porphyry samples have been noted in several studies comparing high-precision CA-ID-TIMS data with in-situ data (von Quadt et al., 2011;Chiaradia et al., 680 2013;Chelle-Michou et al., 2014;Chiaradia et al., 2014;Correa et al., 2016). As discussed above all presented datasets are considered accurate and thus the discrepancy in dates is most likely the result of differences in the statistical handling and geological interpretation. As there is no evidence for any systematic errors jeopardizing the accuracy of any of the three methods in this study, all methods are considered accurate and the reason for apparent discrepancy must lie in the geological interpretation of the statistical uncertainties. 685 The protracted zircon crystallisation identified at Batu Hijau has profound broader implications for the determination of magma emplacement, crystallisation or eruption ages. Extended magma reservoir lifetimes are not unique to Batu Hijau but a commonly described feature (e.g. Miller et al., 2007;Claiborne et al., 2010a;Reid et al., 2011;Buret et al., 2016). A weighted 700 mean is a measure to quantify the mean of a population whereby emphasising the importance of values with low uncertainties over those with high uncertainties (Reiners et al., 2017) and is only allowed to be usedvalid in cases where the data is normally distributed around the one expected value (Wendt and Carl, 1991). This is rarely the case when investigating geological processes and indeed, Tthe presented in-situ data-sets record protracted zircon crystallisation (>300 kyr ) in the magma reservoir that results in zircon population distributions that cannot be easily defined statistically (e.g. by a normal distribution: 705 Fig. 5, 7: cf. Keller et al., 2018), negating a normal distribution around a single geological eventthe emplacement age. The calculated weighted mean thus does not represent the porphyry emplacement age but rather represents the mean of the duration of the average zircon crystallisation, This is corroborated by the weighted means of the LA-ICP-MS and SHRIMP dates 29 approximately describing the mean of the zircon populations defined by CA-ID-TIMS (Fig. 11). Therefore, the calculated weighted mean dates of data sets with a large number of dates but low precision do does not necessarily describe any specific 710 geological event, especially as the uncertainties indicated by the standard error for the LA-ICP-MS data are too small to even cover the entire recorded duration of zircon crystallisation. It has to be noted that more complex settings where xenocrystic zircons overlap within uncertainty of the in-situ techniques with the auto-and antecrystic zircon population (e.g. Chelle-Michou et al., 2014) would result in even less reliable geological dates estimated by in-situ techniques. Therefore, using the weighted mean of a zircon population to determine emplacement or intrusion ages can be a broad oversimplification if dates do not 715 represent a normal distribution around the dated event. Similar problems can occur when calculating eruption ages for nonhomogeneous zircon populations from tuffs or other volcanic rocks (Schoene, 2014).
Traditionally, problems associated with the oversimplification associated with calculating weighted means and their standard errors in geochronology were hidden by the larger higher uncertainties resulting from larger higher analytical uncertainties and smaller sample sizes. The standard error of the mean is a measure for the reproducibility of an experiment 720 (i.e. how likely is it to obtain the same weighted mean if the same amount of zircons from the same sample are analysed again) but one of the main assumptions for using the standard error as the uncertainty of a weighted mean is that the data is normally distributed around the expected value. Due to rapid data acquisition nowadays, by in-situ techniques, calculated standard errors can result in uncertainty envelopes of <0.1% for a sample. In the case of the LA-ICP-MS dates from the Pliocene Batu Hijau porphyry intrusions the standard error of the weighted mean (~1%: ~40 ka) is on the same order of magnitude as an individual 725 CA-ID-TIMS date and therefore smaller than the geological spread of zircon crystallisation ages dates, which negates a normal distribution of the zircon data. The combination of using a weighted mean to describe a non-gaussian sample distribution with the very small attributed uncertainties attributed to a weighted mean results in highly precise dates that may have no relation to a specific geological event.
The MSWD (A reduced chi-square statistic) of a data-set provides a first measure to indicate whether your dates are 730 normally distributed around an expected value and thus whether the calculated weighted mean and standard error are of significance (√( 2 −1 ) rule by Wendt and Carl (1991)). As discussed before, the MSWDs for the LA-ICP-MS data are elevated, suggesting an underestimation of the individual uncertainties or, in this case, that the data do not represent a normal distribution, and thus implying that weighted means and standard errors should not be calculated to characterise a geological event. However, the MSWDs for the SHRIMP zircon analyses of the Intermediate and Old Tonalite are within the 95% 735 confidence interval of the MSWG acceptable, mainly due to the higher larger individual uncertainties. Still, they are similarly affected by protracted zircon crystallisation, which biases the weighted mean to higher values (Fig. 11). Furthermore, overestimated individual uncertainties can result in acceptable MSWDs but similarly inaccurate dates and low standard errors.
For example, increasing individual uncertainties for the 206 Pb-238 U dates obtained for the Old Tonalite by LA-ICP-MS by a factor of 1.5 would result in an acceptable MSWD (0.95) but the weighted mean and standard error would be nearly identically 740 precise but inaccurate (3.880 ± 0.041, 2SE) to those calculated with the actual uncertainties. Based on the presented data it is 30 advised not to characterise a geological event by a weighted mean with an associated standard error if the MSWD is elevated (Wendt and Carl, 1991) and if presented it should be referred to as date and not an age. Even if the MSWD of a dataset is acceptable this is no absolute confirmation that the presented date is accurate within the presented uncertainty, unless there is evidence that the data are uniformly distributed around the dated event or uncertainties are sufficiently high. 745 An attempt to obtain reliable porphyry emplacement ages from convoluted datasets could be to apply the weighted mean on the youngest or geochemically most evolved population of zircons. Differentiating zircon populations based on geochemical affinity could potentially work in situations where there are clear temporally resolved chemical trends (e.g. Wotzlaw et al., 2013;Samperton et al., 2015;Large et al., 2018). In most scenarios however, there are general geochemical trends but they are strongly convoluted on a temporal scale (e.g Schoene et al., 2012;Rivera et al., 2014;Buret et al., 2016). 750 For example, at Batu Hijau early crystallised zircons can have the same chemical signature (e.g. Th/U: Fig. 6) as some of the youngest zircons. In summary, identifying the youngest zircon population (e.g. by its geochemical signature) and applying a weighted mean to it could significantly increase the accuracy of the calculated emplacement age but it requires a detailed understanding of the geochemical evolution of the crystallising magma reservoir.
Based on the presented data we would recommend to use an uncertainty attributed to the weighted mean that is more 755 representative of the uncertainty of the individual analyses, so that it will most likely cover the actually dated event. Here, we tested the standard deviation of zircons dates from each sample as a measure for the uncertainty of the weighted mean. This approach would giveprovides a more realistic estimation of the uncertainty associated with calculating a weighted mean of a geologically young data-set as it describes the variability in the measurements, (0.29 -0.62 Ma// Fig. 7, 11) and, importantly, it would be independent of the number of analyses. The resulting values at least for the Pliocene Batu Hijau deposit results in 760 appropriate uncertainties for the weighted mean, as it would cover an appreciable part of the range of in-situ dates and thus the >300 kyr of zircon crystallisation and the emplacement age. Another approach would be the calculation of the dispersion of a data-set (Vermeesch, 2010(Vermeesch, , 2018 where not all data is treated as part of a single population but where the possibility of data dispersion of the analysed sample set is considered. For the presented LA-ICP-MS data-sets this would result in apparent dispersions of 212 +43/-39 kyr, 229 +43/-39 kyr and 191 +41/-36 kyr for the data of the Old, Intermediate and Young Tonalite, 765 similar to the actually recorded durations of zircon crystallisation. However, this approach requires a precise estimate of the associated individual uncertainties. Similar to calculating the MSWD, over-or under-estimated uncertainties would significantly modify the result. The presented data highlights the importance of CA-ID-TIMS zircon U-Pb geochronology to resolve complicated complex zircon crystallisation patterns., which in turn allow to adjust in-situ techniques. While the individual LA-ICP-MS 770 data appear to be accurate (Fig. 11), weighted means and standard errors of high-n datasets (e.g. 3.879 ± 0.039 Ma for Old Tonalite) may provide precise mean zircon crystallisation ages but are likely to be inaccurate in determining emplacement or eruption ages if there is only a minor degree of protracted zircon crystallisation. Taking into account the dispersion of the dataset (e.g. 212 +43/-39 kyr for the Old Tonalite) or using the standard deviation (320 kyr), results in estimates of the emplacement age that overlap with the emplacement age suggested by ID-TIMS and appear to be a more honest way of treating 775 31 the data. The resulting emplacement ages may not be precise enough to resolve short timescales but can provide a timeline of broader scale magmatic events. In the case of porphyry research high-precision ID-TIMS dates are required to resolve the durations of porphyry emplacement and hydrothermal processes but in-situ data can reliably reconstruct a timeline of magma emplacement events within porphyry districts over by Myr timescales (e.g. Rezeau et al., 2016). More generally, it is understandable that the highest possible precision is strived for from a single dataset. However, it should be refrained from 780 increasing the precision purely by statistical measure without valid assumptions or knowledge that the boundary conditions are met as this can result in hugely precise but inaccurate dates. Furthermore, combination with in-situ petrochronology techniques (i.e. U-Pb isotope and geochemical data from the same analyte) allows to screen zircons for inheritance and more importantly provides spatially resolved geochemical information that can be integrated with high-precision dates.

Conclusions 785
High-precision zircon geochronology by CA-ID-TIMS combined with in-situ zircon geochemistry provides valuable datasets that allow the reconstruction of geological processes with the highest temporal resolution. At Batu Hijau zircons record the magmatic to hydrothermal evolution of the world-class Batu Hijau porphyry Cu-Au deposit from the onset of zircon crystallisation to emplacement of the post-ore Young Tonalite. The magma reservoir that sourced the tonalites and the Cu-Au mineralising fluids records zircon crystallisation over 336 ± 27 kyr. Emplacement of the first exposed tonalite at the Batu Hijau 790 deposit (Old Tonalite) occurred after 246 ± 28 kyr of uninterrupted zircon crystallisation in this subjacent reservoir. Zircon trace element signatures support a dominantly crystallising and cooling magma reservoir over 285 ± 24 kyr until emplacement of the Intermediate Tonalite. After emplacement of the Intermediate Tonalite the chemistry of the reservoir remained in rather steady conditions for 51 ± 28 kyr during which it could have been disturbed by magmatic recharge or underplating until final emplacement of the Young Tonalite. Ore formation is most probably associated with the last stages of the chemically and 795 thermally evolving magma reservoir. The maximum duration of ore formation can be constrained to <122 kyr by the emplacement ages of pre-to syn-ore Old Tonalite and the post-ore Young Tonalite. This maximum duration of ore formation covers different pulses of mineralisation that could have lasted only a few kyr. We record a magmatic system that was active over ~250 kyr before emplacement of the first porphyry intrusion and onset of several pulses of hydrothermal activity forming the world-class ore reserve in less than 100 kyr. 800 Comparison between in-situ LA-ICP-MS and SHRIMP as well as CA-ID-TIMS U-Pb geochronology reveals that all techniques provide accurate individual dates (within the stated confidence interval). However, statistical treatment of in-situ data by calculating a weighted mean and standard error can result in highly precise but inaccurate older ages of questionable geological significance with apparent uncertainties that do not provide an accurate measure for the uncertainty of emplacement age and therefore geologically meaningless ages. The tempo of magma evolution and hydrothermal processes associated with 805 magmatic-hydrothermal systems, such as porphyry deposits is too fast to be reliably resolved by currently available in-situ U-Pb geochronology and requires ID-TIMS geochronology. Combination of high-precision geochronology with in-situ or TIMS-TEA geochemistry is currently the most powerful tool in deciphering these geologically rapid processes.

Data availability 810
All data used in this manuscript is available from the supplementary files.