Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. igdsgsfrln-itnetae,admdfidvso ohl oaepe eo ae Vte Sherley, & (Votier seawater, water from below Brooke, salt prey 2017; excess locate help Sherley, excrete to to & vision glands Votier modified salt tonnes/year, and euphausiids), as travel, fish, million such long-distance flying (70 for traits anchovies, designs unique productivity wing (e.g. have ocean’s seabirds species Physiologically, the cycle forage life of pelagic 2001; 2004). their Holt, on complete 7% Procellariidae, & predominantly over Sulidae, Crooks feed the consuming (Estes, and as such ecosystems sea & families marine (Votier at Some in breeding primarily 2006). and predators Fiedler, feeding top & for considered Pitman ecosystems usually Ballance, marine are on and depend 2017), that Sherley, species avian all encompasses Seabirds INTRODUCTION 1. programmes. risk eradication the maximising of eradications thereby impact to and successful conservation colonies lead after the between can extension and competition range success recolonization minimising predicting of areas, island these analysis subsequent in Our and threat-mitigation anticipatory eradications competition. enables subsequent increased species changes with Invasive and through islands gains possibly distribution. infested distribution, distribution from prey seabird predictable in eradicated We and shifts are productivity islands. cause rats nearby may regional where on oscillations abundance in scenario presence Climate islands, rat in a to conclusions: by under increased Main influenced closer sea significantly Procellariidae recolonization. km at not seabird contrast, were 44 abundance In and densely increased and km of more 16 islands. 83 areas at at aggregated rat-infested identified plateauing thresholds to families islands, The (distribution to with Both distance proximity compared Index. greater greater island. island Mode with in to rat-free Dipole and distance to the respectively) next greater relationships by higher respectively) with represented positive times as abruptly documented 1.25 We declined Dipole, and Ocean Sulidae (1.08 families. Indian and seabird the Laridae and all and rat-free of abundance for both abundance oceanic drivers identified Procellariidae to We to proximity and oceanographic Results: models of Sulidae and additive distribution. effects between geomorphic in generalized the thresholds common quantify used point and We to breaking trees identifying hotspots season. distribution, regression seabird breeding oceanographic boosted on geomorphology, the built islands Procellariidae), during We rat-infested and 2017 oscillation. Sulidae, to observations climate (Laridae, sea 2012 and families At variability, from seabird Methods: dominant collected seabirds Ocean between of were Indian distribution relationships Central 425) the Territory, identify affect Ocean = islands Indian (n on British infestation seabirds Archipelago, rat Chagos of and The oscillation climate Location: which to sea. extent at the document to aim We Aim: Abstract 2020 5, May 4 3 2 1 Letessier Perez-Correa Julian oceanic influences distribution invasion seabird species alien and oscillation Climate nttt fZooyo h olgclSceyo London of Society Zoological the of Zoology of Institute Australia Western of University London of Society Zoological Santo Espiritu Universidad 4 1 ee Carr Peter , 2 esc Meeuwig Jessica , 1 3 ete Koldewey Heather , 2 n Tom and , Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. ta. 99 eda ta. 03 hpad&Sepr,21) h rhplg scniee fgreat of considered designated is ten archipelago and The breeders, resident 2019). of Sheppard, species & eighteen Sheppard harbouring 2013; (Everaarts conservation, undisturbed al., seabird relatively the et therefore of for is In majority Readman and importance The 2005). 1971, 1999; 2010. Jaquemet, since in al., Indian activities & area human British et Corre protected to the marine closed (Le within no-take been encompassed seabirds a has islands, Le designated to archipelago tropical 2014; was important 55 which al., particularly comprises (BIOT), et Territory Archipelago are (Danckwerts Ocean Chagos biodiversity which 2012). the marine of al., IO, of et central most hotspots the Corre 2012), considered Le al., are 2015; et that Holmes, archipelagos Corre (Hutton, & 27 recovery Russell has population 2009; IO seabird programmes al., The and eradication et restoration Towns Rat food island 2007; 2008). successful as Sinclair, al., of such & et component factors, Parkes, Jones major of 1972; a are combination (Woodward, burrows considered a in predation are nesting both upon rat seabirds At cause depends small to 2007). example, can infestation vulnerable For do Diamond, history. and rat particularly new life & to adults and of Charette to weight prefer and impact Jones, body chicks adapting strategy, and the Major, breeding both availability, quickly level, breed 1985; on King, species by to prey 1972; seabird islands Rats and (Fleet, the diet. invade rest extirpation omnivorous successfully and to their declines Rats islands of population 1985). because need part (King, Seabirds in disturbance 2008). habitats, rat al., limited ship et with the Jones both 2003). Yamagat, as 1985, & such (King, Guan rodents, populations (Ashok, ecology discovery by seabird recent invasion between relatively Island linkages its Weimerskirch, identified & to has yet Inchausti part dynamics have Barbraud, in This Rivalan, Matysiokov´a, seabird studies due 1999). 2013; & and few 2010), Stenseth al., positive oscillations (Tryjanowski, 2014), a et climate Dipole Oro, reflects in (Saji value the of in oscillations index and influence Dipole (reviewed negative by the IO studied or characterised Although positive well the respectively. a degree as been where Dipole large to Index, IO referred a Mode negative Dipole basin, to or the western is by and represented IO is eastern gradient tropical the the between gradient in IO variability SST the and climate 2018), and Bejder, 1999). Interannual Yamagata, & Wandres, & Vinayachandran Christiansen, Goswami, Multiyear Sprogis, oscillations (Saji, (ENSO; climate unclear. a inter-annual Dipole Oscillation remain of Ni˜no from Southern influence distribution derived El the seabird data about as information in distribution such useful variability seabird with year-to-year on managers provide of relied could drivers studies studies time, both (2014), in Since snapshot week). al. single (1 et ( short-term conditions, Laran, term the oceanographic long over Mannocci, persistent the averaged to limited. over influence related Islands. values closely the is time-averaged was sub-Antarctic identifying IO that to Southwest (IO) IO, and the proximity southern in Ocean of and distribution the seabird Indian 9% in (SST) that distribution ranked found the temperature seabird 2019). criteria surface in of (IUCN, List drivers sea distribution Extinct explored of Red seabird as (2007) IUCN 1% of al. and the et drivers Endangered, Hyrenbach to Critically oceanographic according as regarding Hammill, seabirds 6% (Paleczny, Information Endangered, of declining as listing families are A these Procellariidae, seabird from and global 2015). species of Sulidae Pauly 69.7% that Laridae, and production revealed fishing assessment energy families Karpouzi, recent in pollution, the A water entanglement change, including 2012). include al., climate makes humanpopulations, threats et fisheries, (Croxall web and Human via species trophic prey mammal conditions invasive 2009). seabird oceanic environmental and of Einoder, overexploitation and in 2007; sea, changes terrestrial at Wiese, Balance al., large-scale gear both & Vilchis, et and linking Sydeman 2007; Laran, long-term (Piatt, role Jr, Mannocci, of activities ecological Hunt 2014; indicators temperature, & important al., sensitive Metzl, Their surface et Weimerskirch, and seabirds Catalogna, Veit, sea strategies 2006). Mannocci, Hyrenbach, foraging Fiedler, 2017; 2013; their (e.g. & al., Morgan, of et conditions & (Fox reflective Maxwell oceanographic prey depth), 2014; their to slope, of linked distribution (e.g. 2018). closely the al., characteristic Love, et is geomorphic & Graham Ganning and sea 2006; chlorophyll-a) III, al., at (Loder et distribution Fukami cycling 2004; nutrient Seabird Stewart, such and function & pr > atsrattus Rattus er)wr oepeitv fdsrbto hnthose than distribution of predictive more were years) 7 2 soeo h raettrast seabird to threats greatest the of one is , Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. on a uaino 0mnts uigwihtevse yial tae t1 nt n travelled and knots 12 = (n at aggregation steamed feeding typically seabird vessel any the during transect which opportunistically Each generated during (1984). gene- were Blaker, minutes, were & counts vessel 329) 30 Dixon Aggregation marine = Jones, of km. Tasker, a (n duration c.11 of counts from method a Transect conducted the generated: had were adapting Research were count by 425) IO System types transit, Earth = the vessel sample NOAA (n during different and (2017; rated samples Three reserve event three count expeditions. marine by positive followed Seabird six very BIOT was during 2017). one which the the by 2013), ESRL], of sampling, and and et [NOAA 2012 phase of (2014-2016) (Carr, Laboratory (during events months Archipelago moderate Dipole Dipole the Chagos IO the IO positive the conducted During neutral with modestly in was 2015). of overlap activity survey seasons Carr, to two breeding The distri- 2011; experienced April, peak sea. seabird Carr, with and at on 2019; coincides November seabirds infestation al., generally between of rat period archipelago 2017, island This the to and monsoon. of 2012 conditions survey from oceanographic multiyear conducted of a influence conducted we the identify bution, to order 28 In of mean observations yearly Seabird a 2.2 with approximately an March–April has and temperature Garbe-Sch December–January surface & Sea in Zinke north-west the September). Dullo, maxima the in to (Pfeiffer, from with Situated (May generally south-east 1999). distribution winds the (Sheppard, tropical, moderate bimodal and is monsoon has April) climate reversal archipelago to The the seasonal (October 1999). (ITCZ), the Sheppard, zone and & convergence Dumbraveanu conditions inter-tropical 2011; oceanic Chagos (Carr, by Great meters characterised the 6,000 on over km and depth 60 Egmont, maximum islands approximately Salomon, km Fifty-five combined Banhos, 2012). 60,000 Peros constitute (Carr, approximately Garcia, and mass Diego land 1a) continental of (Figure nearest atolls Bank the the 6 from within at km clustered IO 1,500 are over central is the and in ridge, located Laccadive is Archipelago Chagos The Area Study 2.1 METHODS 2. we infestation, priorities. distribution rat seabird restoration predict to possible island climate we and identifying vulnerable Finally, habitats, with for under-utilised sea. and currently relevant linkages at identifying factors island distribution scenario, possible eradication seabird on rat explore on archipelago-wide, infestations dependent an and under rat are hotspots of effect seabird habitat the that ocean determining determine in reveal recognising of variables drivers 2007) to Then, oceanographic identify al., and to order et oscillation. reserve geomorphic Hyrenbach marine in of 2014; BIOT influence distribution, al., the the et within identify seabird Laran, 2017) to to seek Mannocci, 2012 first (i.e. We (from IO survey distribution. the seabird in multiyear a done using work by previous on expand we been (BIOT Here, 2019). plan therefore al., management from has recover et BIOT eradicated successfully draft eradication may (Harper were the 2017 Rats Rat reefs of 2019). in 2019). and framework subsidised prep. conservation in subsidies Graham, these framework the nutrients conservation & Notably, within to management target Wilson leading reefs. priority islands, (Benkwitt, coral a infested bleaching designated adjacent on densities coral seabird than on following that greater Pitman, function found faster times & (2018) and 760 Carr al. to productivity et (Harper, Graham up populations increased 2010). were seabird Cuthbert, islands the & rat-free affecting Hilton on negatively 2015; Bunbury, area), & island cats Harper the 2019; feral of 18 (i.e. (95.3% the 2008; islands Godley, mammals of invasive & 55 turn Broderick the other McGowan, to and 2010; dating Cuthbert, plantations, rats & coconut (Hilton Historical Areas’ 2006). Birds Carr, ‘Important proposed two and 2 fsalwpoi ef,ad5000km 580,000 and reefs, photic shallow of neg 2009). ¨ onberg, ei catus Felis 3 ° n 72 and S ebnSih&Cre,21)o 6o the of 26 on 2016) Carter, & Wenban-Smith ; 2 fln ra h ertr encompasses territory The area. land of ° 2 ttesuhr ii fteChagos- the of limit southern the at E fpiaiyoenchbtt iha with habitat, oceanic primarily of th etr,ldt nettoso ship of infestations to led century, ˆ l ah Marine Vache Ile ° C Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. ftepi a ul ihteadtoa nlso ftevral dsac otecoetrtfe islands in rat-free abundance, closest maximum model the theorised first to its the ‘distance at addition, variable distribution In the bird GAMs. of represent the inclusion to by additional considered selected the was variables (Appendix with families model of large Procellariidae built This set and adapt Hastie, was (km)’. the Sulidae & and pair Laridae, using Leathwick combine the the fitted for (Elith, to were of each optimization fitted models boosting were performance The use models enabling BRT S3). that advanced of models, 2000) an pair tree considered A Tibshirani, simple 2008). are infesta- BRT & relatively rat (BRT). sensitivity Hastie Trees of of this Regression effect (Friedman, numbers the that Boosted regression modelled using and We of sea islands islands. at form infested on distribution to rat-infestation seabird adjacent on water to tion the sensitive in is distributions distribution seabird restricts seabird infestation that hypothesise rat We uncertain of with effect species the for Modelling distribution This 2.4 grid. capture resolved 2008). to degree Thuiller, order decimal & in (Wood, 0.4 Hannah, 2017. coefficients x Thorne, trade-off in (Seo, 0.4 model reasonable sampling, sizes a of a of range on matrix year considered uncertainty covariance last modelled Bayesian is the and the resolution at predictions et from set (Yates rendered derived area predictions We was sampled 2006). rendered model predictions our we each beyond that retained, predictions for ensured was meaningful Uncertainty This [year] generating model. Whenever extrapolating whilst avoided each reserve 2018). model, we build approach, marine the al., this to BIOT of Using the used range conditions. environmental variables by the similar beyond defined the with areas hull of in convex values made the only range were to the limited by were restricted areas and unsampled in 2014). predictions al., Spatial et three Laran to (Mannocci, limited Predictions overfitting were avoid GAM Splines to 2.3.2 2006). and (Wood, the sense model using ecological the fitted maintain fitting were to when GAMs order We internally in models. (GVC). smoother knots the score each of cross-validation for power generalised freedom explanatory lowest of the the evaluate with to models mgvc deviance the explained as retained level the abundance) and sea highly used (2014) year, avoided for We al. slope, proxy [CHL]). (depth, et r (a concentration variables Laran, coefficient, chlorophyll-a sample six and (Spearman of per [SST] variables four count (Ap- temperature correlated of surface family types combination sea sampling individual possible al., [SLA], different all using anomalies variables et the against fitted oceanographic variables, Laran, for were and response accounting Mannocci, GAMs the geomorphic 2006), 2014; The on Wood, al., S2). based (GAM; et pendix modelled Models Catalogna, were Additive requirements, (Mannocci, grouping distributions Generalised ecological needs This seabird using similar counts. energetic oceanic have our or The taxo- species increasing habitat-use high-level 2014). similar by comparatively to taxonomically power seabird This relation that abundant statistical variables. in and assumption more response frequent the generate our most requires to as the approach us area selected allowed we protected classification seabirds, marine of nomic BIOT distribution the oceanic in the families model to order In variables Response 2.3.1 modelling 1b-1g). habitat (Figure Oceanic reefs shallow were 2.3 Observations the 2011; bias. and Carr, by of (e.g. islands source conducted Archipelago the potential the were a to within eliminates proximity observations stationary seabirds observer in seabird was on in made consistency expert vessel All predominantly This an the S1). 2015). and Carr, manuscript when Appendix 2012; this 180 generated 1, Carr, of a 60 were co-author Figure within duration a 9) 1, generated Carr, (median = (Table were Pete counted samples (n meters been All counts 300 had min). point approximately birds 30 Finally, all duration 2016). until count counted al., (nominal were et aggregations Letessier the min; within birds The 87). akg nR( eeomn oeTa 07vrinRvrin333 htdtrie h degrees the determines that 3.3.3) version R version 2017 Team Core Development (R R in package > .0and 0.60 4 < 06)i h aemdl olwn Mannocci, following model, same the in -0.60) ° r owr ftesi,otto out ship, the of forward arc Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. oepoone nplgcaddee ra Fgr b ) n naeswt nemdaesoe(.15 (c. slope intermediate with areas in and e), 5b, (Figure areas levels deeper abundance and higher pronounced pelagic signature with was abundance in uniform depth Laridae pronounced more f). seabed and more was ( 5c strong (Figure distribution seabeds Archipelago a Procellariidae shallow the of revealed over while northwest the distribution e), towards and and Sulidae land near d, and b, Laridae 5a, for (Figure predictions 4). Archipelago model (Figure Chagos 2017 Spatial to the 2015 within from consis- Predictions increasing respectively) Spatial an deviance 3.2.2 2015, 20.47% to and 2012 (28.68 from variability abundance yearly in decreasing high were tently 3b, showed chlorophyll-a Figure Procellariidae and 23.97%, Sulidae. and and temperature the Sulidae (24.31% surface not Procellariidae but Sea for 3j) deviance. and and the 42.60%) 3h and of 3d, (13.11% Procellariidae 31.24% Laridae the explaining influenced for anomaly variables 3i), was level important and distribution sea variables, Sulidae respectively 3g oceanographic for Sulidae 3c, of important and terms was (Figure In that Laridae variable 3f). of geomorphometric Figure distribution other (28.68%, the only slope Procellariidae. The in for 3e). deviance 21.2% and 33.64% and 3a Sulidae and (Figure for 42.90% 46.3% Laridae, explained for depth 33.7% was Seabed GAM each for explained deviance Total distribution of drivers respectively. Oceanic ind.), 3.2.1 (no 2013 and sample) Modelling per Predictive ind. respectively samples), (3.2 3.2 per 2014 ind. sample), (16.3 2012 per and ind. sample, (16 per sample (24 2015 per 2017 in individuals sample), lowest Procellaridae, per and and ind. (33.1 Sulidae, 2013 for Laridae, in retained the highest For were was families 2). These (Figure Procellariidae individuals). modelling (872 (8,817 distribution (boobies), (northern Laridae Procellariidae further the and Sulidae Hydrobatidae by individuals) across dominated (5,057 terns), (frigatebird), were Sulidae 2) Observations and individuals), Fregatidae (Figure storm-petrels). (southern 2017 (noddies (tropicbirds), Oceanitidae and Laridae and Phaethontidae 2012 storm-petrels) recorded: between petrels), were expeditions and six families (shearwaters the Seven during observed samples. were all seabirds 15,063 total, In sightings Seabird 3.1 lost net and RESULTS gain nearest net 3. showing the infested, where be only will mapped islands were new rat-infested predictions no the The that wide from distribution. assume models. archipelago resulting seabird we rat-free an in predictions since of the confidence the rat-infested scenario of 95% of was a predictions island difference the following the the with abundance from subtracted seabird determined models we the in were whether programme, gain (BP) and net eradication break-points families the rat between islands, determine differences rat-free To rat-infested 2014). significant to (CI). al., find and distance intervals To et the rat-free test. D’agata by Davies’ was 2008; influenced a al., is island using et distribution islands, seabird (Elith rat-infested which trees and or to of (2008) (break-point) numbers al. thresholds and et counts identified rate Elith We transect learning in between used code trade-off we the a variability, m adapting using reduce (in and fitted variable To methodology availability. area to the landmass island ‘distance following variable nearest of the fitted the a were effect of included BRTs potential inclusion only. also additional we the samples BRT the for each built For account was BRT (km)’. to second islands The rat-infested effect. closest rat the any of absence the gbm akg nR( eeomn oeTa 07vrinRvrin333.TeBTmdl were models BRT The 3.3.3). version R version 2017 Team Core Development (R R in package < 00m npoiiyt sad n tls(iue5,d.Sldeaudnewas abundance Sulidae d). 5a, (Figure atolls and islands to proximity in m) 1000 5 2 º ), , Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. yig 07 aumt eCre emrkrh 04.I iewt hoeia xettosdet their day to & due same Nicholson, expectations the (Surman, theoretical during foragers with line multiday islands In or to 2004). long-distance Weimerskirch, returning not & (Carr, and and Corre, are previous foragers leaving Le they with depth Jaquemet, lagoonal noddy consistent suggesting 2017; also to mostly lesser Ayling, season, are and be breeding related results noddy Our the to strongly ( brown in observed here. was distribution water the been modelled shallow of noddy, previously their observations over with have brown consistent and Archipelago comm), the islands, Chagos pers. by around the concentrated dominated in abundance Laridae Laridae, modelled the with Archipelago chlorophyll-a, of Chagos the distribution within The distribution seabird shifts of distribution strategies. Drivers restoration in island result 4.1 have for can and and eradication conservation distribution, how seabird and seabird tropical Information oscillation, for on scenario. have climate implications rats We eradication critical to rat without 2007). has archipelago-wide sensitivity al., and an hotspots, under et with abundance seabird Hyrenbach in islands 2014; on increase of al., net et of impact areas Laran, investi- explicit identified (Mannocci, previous spatially unbalanced IO complementing for MPA, the southern a Accounting BIOT has and modelled including the southwest and within the distribution, oscillation. hotspots conditions in Dipole seabird seabird environmental gations IO identified in driving have the of trends we conditions and range effort, spatio-temporal abundance oceanographic sampling broad regional identified and between a have geomorphic association we spanned identify possible Archipelago survey to Chagos multiyear us the Our enabled in distribution. sea at seabird observations our Through uniformly DISCUSSION and minor 4. were Procellariidae This for 7l). Gains – 7g (Figure k). families This islands 7 seabird larger 7f). all (Figure near 7l). – eradication pronounced Laridae (Figure 7a rat most distributed for (Figure Following was pronounced families gain 7e). seabird The are particularly and all was 7). points 7b of (Figure (Figure breaking abundance abundance Laridae Threshold in the for increased reduced pronounced 78.4]). islands more nearby 68.6, was 82.9 on 60.54 pattern [CI the (BP rats and for km island of islands detected 73.5 presence rat-free rat-free was between The (BP S3). islands for CI (Table islands nearby 21.1] the S3 rat-infested on in 11.9, Appendix presence and in difference [CI rat 96.4]) significant reported km of no 82.9, rat-infested 16.51 effect showed for [CI at No all BP km km was 63.6 for the 67.3]. at apparent Sulidae as 54.0, and were family, for 50.2] [CI islands 44.8, Procellaridae BP islands [CI of rat-infested The islands effect rat-free for the infested for 67.9]. km km whether in 59.1, 47.5 island, BP at nearest [CI Thresholds was the Laridae islands which seabirds. for regressions to BP of stick threshold The broken distribution the by families. 6g). the indicated revealed – (BP) influenced as and 6a points the islands, not, Figure 36%, Breaking rat-free in or 5%; to 6i). higher proximity was [?] [?] – was the 6g Procellariidae island island to Sulidae (Figure sensitive and nearest rat-free 48%, were 11%, the families a of [?] seabird [?] to Sulidae All area (Laridae 8%, the Distance by respectively) island [?] by explained 36.1% (Laridae rat-infested explained deviance – models Conversely, to Deviance rat-infested rat- 32.5 Distance 15%). a 48.5%, by to - %). [?] Distance that (39.3 Procellariidae 14.6 12%). Sulidae than (0- and [?] higher Procellariidae Laridae Procellariidae consistently for and the 20%) important 31%, with was [?] [?] compared Procellariidae island Laridae and rat-infested 59%, 37%, or [?] [?] free Laridae (Sulidae 71%, models [?] rat-infested (Sulidae than deviance more explained models BRT Rat-free presence rat S2). to (Appendix Response specific 3.2.3 family Lakshadweep-Maldives-Chagos and the spatially along was pronounced uncertainty was prediction distribution Model Sulidae ridge. and Laridae Both 5b). Figure 6 < 0 m). 100 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. eoeyo va ouain Bok,e l,21;Jnse l,21;Lvr,Wlo,&Dna,2010). Elliott, Brink, Donlan, den Van & of 2019; Wilcox, (Pickrell, application wildlife Lavers, the and 2016; pets, requiring and livestock, small al., preservation 2018), humans, a (Warren, the to et risk expensive on for Jones a and strategy posing methodologies 2018; challenging rodenticide powerful appropriate al., toxic technically a et and is as (Brooke, eradication eradication attempts recognized However, latter populations of increasingly 2006) The avian feasibility is (Meier, 2019). of the eradication Island al., recovery et test rodent Eagle (Harper Island on to Jacobin attempt islands and scale. failed Sel small du a on Marine, include Vache focussed Iles Archipelago on Chagos attempts the successful and in efforts eradication programmes Past eradication rat the for that Implication likely (Gaston, 4.2 it families makes other Procellariidae the for the that than et of pronounced (Wakefield likely 2007). abundance less overlap Smith, lower very is & proximity foraging and therefore colony Ydenberg range minimise from it unless distribution resulting to 2017), makes distribution pressure wide behaviour al. respectively), competition The Sulidae et different km Mendez and 2013). express with 176.0 Laridae line colonies ( al. colony and (in abundant the different together compete of km the Within therefore close from function 100.7 and both clustered individuals distribution which a 1987). are in (i.e. overlap to as Montevecchi, and colonies islands range vary apart neighbouring & from The km to Cairns out 100 expected Goulet, atolls. than radiates is Birt, within less Halo islands) otherwise are (Birt, The colonies, islands between range around many foraging zones 1963). Archipelago, depredation bird Chagos (Ashmole, prey and a Halo size, to to Ashmole’s lead proximity, failed km The to have 3500 expected could as to is range known presence. (up prey sampling rat family over our to this competition which related Constant 2009), of shift ground Phillips, range distribution in & foraging any Corre nest mask large no Le they may and found Ramos, capture, because behaviour Catry, we 2002), Seychelles; particularly pelagic Although Vaderwerf, the are The & in species 2015). Polhemus, shearwaters). Procellariidae Catry, (Smith, many (i.e. & predators 2010) distribution, burrows scattered land Granadeiro Procellariidae predominantly al. invasive Alho, on a et to to presence Young (Dias, only vulnerable due rat burrows km; day be of to 67.5 the may return effect islands during Procellariidae significant (i.e. from distribution 1974). Sulidae independent King, foraging remote both appears 1981; wider distribution than and Stone-Burner, a their 1974) & have that Harrison typically King night; km; Procellariidae km; abundance at 80 that in 480 is increase (i.e. this to (i.e. Laridae and for appeared colonies reason Sulidae, nesting and potential from ( Laridae A waters range the islands. warmer to from in contrast ( shearwater distance in areas of with and, number proximity productive greater island in to reporting number sensitive IO, lower western the and in to C) (2014) sensitive al. were ( et warmer Sulidae Laran, preferring ( islands. area, waters (2017). rat-free protected productive marine near less BIOT al. abundance and the across et greater concentration distributed in Mendez evenly chl-a red-footed were aggregating with As Procellariidae Laridae, the of consistent prey. than of were for understanding so range results competition less robust pantropical our although interspecific more the rats and here, intra a across the prognostic by that not on permitting driven was concluded data closely IO) They collected is the identified (Galapagos (2017) distribution equator and distribution. (2017) booby, the determines al. along Caledonia al. colonies that et New five et factors Mendez in Channel, Mendez devices tracking chl-a. Mozambique contrast, Weimerskirch, using and In Islands, boobies & red-footed boobies Potier, of 2005). red-footed chl- Marsac, behaviour Marsac, elevated between foraging Corre, and & correlation Le productivity Jaquemet, negative Jaquemet, high distribution Corre, a 1997; of Sulidae Le Reilly, areas Weimerskirch, with & ridge. associated 2005; Pitman, Lakshadweep-Maldives-Chagos positively the (Ballance, and be concentration along Garcia to Diego a and thought the atolls, of been east Banhos traditionally hotspots has Peros pronounced the with elevated distribution, of in oceanic west resulting primarily rats, a to showed sensitive Sulidae most The group the were islands. Laridae rat-free the near 2015), abundance Bunbury, & (Harper size small < .0m.m mg. 0.20 -3 h-) u bevtoswr ossetwt hs fMannocci, of those with consistent were observations Our chl-a). > .7m m mg 0.37 7 -3 .TePoelria eetegopteleast the group the were Procellariidae The ). > 0e C), 30deg > < 29.5deg 0km 20 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. bnac Mxel&Mra,21;Kmre l,21) ti eodorsoet itnus these distinguish 2019). on to al., data et scope include Letessier our tuna to 2017; beyond Meeuwig, midwater in distribution using & is seabird increase observations, Bouchet seabird of It an the (Letessier, analysis to videography by simultaneously our baited 2016). collected indirectly, both abundance expanding al., predator and Dipole currently and et the abundance, prey are subsurface by we Kumar species however impacted 2013; forage (Oro, here, be in links Morgan, processes could trophic reduction & seabirds multiple a (Maxwell by predators, by abundance mediated subsurface example, likely with greater are for commensal be The megafauna directly, foragers may mobile family As detail. and this more Dipole 2014). suggests in the Dipole between explored the linkage change. be Any to environmental to and global mechanisms variables common to boobies enable oceanographic vulnerable the red-footed will most both on that the deployed which to found being comm.), Procellaridae currently (2018), is of tracking pers. sensitivity satellite (Carr, al. and telemetry BIOT et of in Use Sprogis prey. example, (Champagnon, Picaut, inshore levels For of & lack trophic Lewis, higher ( 2018). of Hampton, dolphin behaviour Anderson, Bertignac, bottlenose foraging & (Lehodey, and is Drummond productivity demography the ENSO, it species Lebreton, as for Archipelago, forage such regional implications oscillations Chagos in influence winds with climate drop the 1997), westerly to a other to In regarding known that leading understanding Chagos is, afield, is and with 2015). further consistent the There which forage pronounced Zhang, be to would seabirds & more in require This speculative. (Du upwelling are abundance regional abundance. events remain IO in drop seabird Dipole must the a positive that why these in possible during upwelling although mechanisms intensity megafauna. equatorial events, in IO possible that on decrease Dipole to evidence Dipole positive the example, present clues during of for at importance some higher is the the is give patterns on with these research Archipelago may correlated of driving been studies mechanisms body has fledgling of Previous breeding-success a knowledge to Albatross While add IO, results 2010). southern our al., the limited, et consistent productivity in Ocean. (Rivaland tuna are While Indian IO Index the between results in Dipole association Index. Our levels positive Dipole a trophic lesser identified index. higher the a (2016), of to ENSO and Ushadevi dipole so & the appeared the Pillai doing and of families Kumar, Procellaridae influence example, seabird both the For the with between of regarding Index, understanding correspondence abundance Mode current no The with Dipole detected the sampling, increase. We of inter-annual of strength years an the degree. the six by at match the followed oscillations closely during initially, climatic to Procellariidae of decreasing therefore and effect Sulidae families for distribution both trends for with abundance test similar to observed We us enable scale. series time impact. multiyear conservation Our Oscillation full achieve ultimate Climate to the of with order rodent considerations, in Influence to of archipelago, approach set 4.3 the wider and in far success a islands feasibility, into all feed the from to dictate rats useful this eradicating that be in to of explored factors Island aim factors aim multiple Eagle here of competition, are results and basis therefore Our the there Islands and on eradication. Salomon that distribution, are the in and in recommendations From overlap Boddam these only potential that Ile study minimise Egmont note Atoll, seabirds. We to in Banhos order recolonizing Lubine colonies. Peros in recovering Ile the in between Bank, and Chagos to Pierre Sud-Est ( Great Ile Ile sea the prioritise and islands in at should Coin remote eradication competition du combined that prioritising Ile spatial This, propose and that Islands, we less study, spatially gain. suggests our impose are distribution of distribution, will eradication perspective greater in colonies) following yield thresholds bird sea will of at islands nearest presence larger distribution (Harper the on inhabited seabird is eradication in with the it that gains as on and that expensive Eradication revealed family-specific, and has complex challenging. analysis particularly palms Archipelago Our coconut be Chagos and to the likely crabs in 2015). land is Carr, of Garcia programme & presence Diego a temperatures the annual of making mean in island high 2015), and largest with 2015), tropics, al., the Holmes, et in & fail (Holmes, to (Russell likely precipitation more constant is Eradication and 2017). Rattner, & Shore usup trunctatus Tursiuops irtdosoedrn togES er,psil u oa to due possibly years, ENSO strong during offshore migrated ) 8 > 0k from km 50 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. oeaddt sdt odc hsrsac r vial o ulcacs in access public for available are research this conduct to used data and code https://github.com/juperez/SeabirdChagos R the of and interpretation STATEMENT analysis AVAILABILITY ecological DATA the the led to and contributed ideas authors the All P.C. conceive and T.B.L H.K., and J.P.C. J.M., analysis. by observations. assisted seabird writings, the conducted conservationP.C. marine inform to prey, CONTRIBUTIONS their AUTHORS’ and predators of ecology strategies. spatial management the and on focuses primarily is research Letessier B. Tom birds. on Perez-Correa Julian BIOSKETCH Marine in Programme Bertarelli and the 2016, to 2015, contributes in work expeditions This field H.K. and funding P.C. for would T.B.L, Science. Foundation We supporting Bertarelli Biodiversity (NERP). for the Marine and Program of the 2017 of Research support by crew Environmental supported the and was acknowledge National engineer, T.B.L. to Government’s Chief like Master, assistance. Australian the and the to work gratefully through hard are their Hub administration We for BIOT vessel. vessels the patrol patrol and BIOT BIOT extractions the variable the to the access with and us support helping for for Curnick David Dr. acknowledge We ACKNOWLEDGEMENTS 5. factors multiple extends identified niche considerations whose successfully practical seabirds, have colonies. have for can breeding to important We eradication terrestrial particularly addition is where beyond In which footprint. rat- identify activities, ecological conservation 2010). should a influence and al., should programmes on to that et impact eradication species Lavers conservation success, invasive distribution 2016; of eradicating greatest seabird probability al., for the and of et impetus cost Jones considerable response as 2018; is such the hotspots al., There new et predicting predicted programme. have (Brooke and at rat-eradication distribution islands a in attempt gain after net first sea of areas at the demonstrated have is We identifying scenario. this for eradication valuable knowledge, is limited, our are To activities human protection. where seabird processes distribution, for inter-annual western seabird how strategies the drives Identifying in long-term upwelling Dipole 2019). 2015). from IO Claereboudt, Dipole al., the & the like et Pfeiffer 2014), decouple Yamazaki, (Paleczny al., may Watanabe, variability et activities (Watanabe, warming (Allen populations IO human scenarios global Seabird change that with climate suggest under has interactions oscillation. evidence globally time-series and and increase climate our to variability to predicted and climatic is condi- related variability IO both Environmental variability oceanographic the to interannual and in vulnerable potential geomorphology elsewhere by identify are efforts driven to previous is complements us BIOT distribution enabled in modelled sea Our at tions. distribution and abundance Seabird remarks Concluding 4.4 sa clgs neetdi eciigadmdligboiest atrsfocused patterns biodiversity modelling and describing in interested ecologist an is aiebooitwt nitrs nbt rpcladplgceoytm.His ecosystems. pelagic and tropical both in interest an with biologist marine a 9 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. 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Switzerland: Cham, . ubro rnet,ageain n on onssmlsmd ymnhadya within year and month by made samples counts point and aggregations transects, of Number eeaie diiemdl txsi ttsia cec) - science). statistical in (texts models additive Generalized o:10.1126/science.aau1198 doi: . 3,4040 o:10.1111/j.1600-0706.2008.17186.x doi: 420-430. (3), ac 2013 March 2013 Count February Point 2012 December Aggregation 2012 November Transect Month Sampling 9-0.di 10.3354/meps08478 doi: 291-301. , h aua itr fKr tl,nrhetr aainislands Hawaiian northwestern Atoll, Kure of history natural The cetfi eot,9 reports, Scientific - - 3 3 - 7 9 11 3 7 40 50 lmt eerh 57 Research, Climate 15 1,18.di 10.1038/s41598-018-38429-y doi: 1887. (1), aieEooyPors eis 315, Series, Progress Ecology Marine aieEooyPors eis 288 Series, Progress Ecology Marine urn ilg,27 Biology, Current cec,341 Science, 1,4-9 o:10.3354/cr01162 doi: 45-49. (1), ilg etr,5 letters, Biology 64) 68-70. (6141), h u,101 Auk, The rnsi clg Evolution. & Ecology in Trends hpa n Hall/CRC. and Chapman niogln rodenticides Anticoagulant 1) 48R5.doi: R448-R450. (11), 3,5757 doi: 567-577. (3), 1,3-3 doi: 39-43. (1), aieEcology Marine . 7-9.doi: 279-292. 251-261. , δ 18 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. pi 2017 April 2016 February 2015 April 2015 March 2015 Count January Point 2014 April Aggregation 2014 March Transect Month Sampling 28- - - - 2 1 8 - 31 3 6 12 10 1 109 - 1 1 92 5 10 16 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. IUE1. FIGURE ebr apigeotwti h hgsAcieaoadteBiihIda ca Territory. Ocean Indian British the and Archipelago Chagos the within effort sampling Seabird 17 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. bnatfmle aia,SldeadPoelria,sadrie ytenme fsmlsfrec year each for samples of number the by standardised Procellariidae, and (b). Sulidae Laridae, families abundant 2. FIGURE here. reported rat-infested been as have considered islands Six purposes representation blue. for count in bird are islands individual and rat-free (b-g) of and status location (inset). red rat the Ocean in uncertain represent Indian coloured with dots the are Black within islands location islands. Rat-infested and and samples. atolls lines), individual black of (a, close-ups area indicates protected marine the of Boundaries ubro niiulsaid yfml umdars l ape a n o h he most three the for and (a) samples all across summed family by seabirds individual of Number 18 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. ofiec nevl nec mohr S e ufc eprtr,SA=salvl nmle,CL= CHL 95% anomalies, the levels represent sea = regions SLA Shaded temperature, surface estimate. sea function = SST smooth the chlorophyll-a. smoother. each represents in graph intervals each confidence in line blue-solid 3. FIGURE mohfntosfrslce aibe o ahsaidfml id e ape.The sample). per (ind. family seabird each for variables selected for functions Smooth 19 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. yteDpl oeIdx(M)vle uigtemnho apig() M ausrpeetteSST the represent 2003). values Yamagata, & DMI (Saji (c). Ocean sampling Indian represented of tropical as month eastern mode, the and Dipole during western Indian value, the the between (DMI) to gradient Index due anomalies event, Mode oscillation Dipole Climate the (b). by Procellariidae and (a) Sulidae 4. FIGURE eryvraiiyi bnac id e ape,a ersne yGMsot ucin for functions smooth GAM by represented as sample), per (ind. abundance in variability Yearly 20 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. cl fteCao rhplg a ,e n fteBO aiePoetdAe b ,adf.Bakspaces Blank f). and d, modelling. (b, for Area used Protected variables Marine the BIOT of the of range and the e) outside c, areas (a, denotes Archipelago Chagos the of scale 5. FIGURE rdce itiuino aia,SldeadPoelria ntelgrtmcsae tthe at scale, logarithmic the on Procellariidae and Sulidae Laridae, of distribution Predicted 21 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. ntemdl ra=ae ftenaetrtfe rrtifse island. infested rat levels or sea rat-free partial = depending nearest each island, SLA the infested on temperature, of rat point surface or area rat-free breaking sea = nearest = 2nd Area the Procellariidae SST The model, to for distance the S3). 102.6. = point on (Appendix Distance and Breaking chlorophyll-a, plotted 82.9 = no CHL islands. and hence and anomalies, rat-free islands significant, 60.5 were from no rat-infested from Sulidae was 188.1 from km for plot 100.7 and 175.3 point and Breaking 16.5 and km islands. 73.5 and 63.6 rat-free were islands were from Laridae rat-infested km for 67.4 from infested and points 176.4 to km Breaking Distance 47.5 plot. and of partial (g-i) islands, Contribution each rat-infested plot islands. for dependence lines) threshold Partial (red not islands point plots. rat-infested breaking was rat-infested the and Procellariidae or in lines) included on (a-c) (blue not rat-free islands island were of rat-free contribution effects 5% of the than vicinity of less the with Variables in contribution, (d-f). relative (BRT) Trees Regression 6. FIGURE estvt fsaiddsrbto opeec rasneo aso eryilns Boosted islands. nearby on rats of absence or presence to distribution seabird of Sensitivity > %teeoei a o eand tpldln eoe oaino 1st of location denotes line Stippled retained. not was it therefore 5% 22 Posted on Authorea 31 Jan 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158049381.11032677 — This a preprint and has not been peer reviewed. Data may be preliminary. itiuingi,adupr8%qatl ftentgi -) ih hddaesidct ra lss to closest areas indicate areas shaded Light rat-infested minus j-l). distribution gain maxima. (rat-free net theorised eradication the the rat of at (d-f), of quantile already island scenario (a-c), 85% islands, rat–infested variable a rat-free upper nearest a under and the as abundance g-i), island to bird distribution rat-free distance in nearest using gain the model net to BRT the distance from using predicted model distribution, BRT rat-infested from predicted distribution free 7. FIGURE rdce ra fices nsaidaudneudraseai frteaiain Rat- rat-eradication. of scenario a under abundance seabird in increase of areas Predicted 23