Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. n Paaye h aa l uhr eiwdadcnrbtdt h manuscript. CNS the JCW, to CP, contributed collection. and data reviewed to authors contributed All PD and data. LP the CP, analyzed authors. LP all and from input with text manuscript authorship of Statement addresses [email protected] [email protected]; [email protected]; [email protected]; E-mail 4 3 Switzerland Birmensdorf, 2 Z¨urich, Z¨urich, Switzerland 8092 ETH 1 affiliations Author gradients Rasmann elevation along Pitteloud varies networks Camille ecological – of structure to The system the climate of of resilience influence the the of reinforce understanding . null may better of in a that . structure allows than way alpine gradients the stronger in a ecological on along species was in networks keystone correlation wired ecological of Documenting the are importance networks . and reduced plant–herbivore found and temperature, We environments, robustness decreasing cold greater elevation. with to In examined with nestedness corresponded we vary and relationships feces, resilience generality These to and of models. applied specialization levels method reflecting in metabarcoding at networks increase DNA interactions plant– an standardized species of a documenting properties Using because structural network challenge. marginal of how methodological study remains a The however, is networks. gradients, interaction sites ecological species multiple of and rewiring geographic structural with along associated structures be to expected are gradients Ecological Abstract 2020 6, May 5 4 3 2 1 Santana Pitteloud Camille along varies gradients networks elevation ecological plant–herbivore of structure The T Zurich ETH Neuchˆatel of University Fribourg of University Center Diversity Genetic Z¨urichETH nto adCag cec,SisFdrlIsiuefrFrs,So n adcp eerhWL 8903 WSL, Research Landscape and Snow Forest, for Institute Federal Swiss Science, Change Land of Unit ucinlEooyLbrtr,Isiueo ilg,Uiest fNuhae,20 Neuchˆatel, Neuchˆatel, Switzerland 2000 of University Biology, of Institute Laboratory, Functional eei iest ete T ¨rc,89 Z¨urich, Z¨urich, Switzerland 8092 ETH Centre, Diversity Genetic adcp clg,Isiueo ersra csses eateto niomna ytm Science, Systems Environmental of Department Ecosystems, Terrestrial of Institute Ecology, Landscape 4 1 Lo¨ıc Pellissier , egoRasmann Sergio , 1,2 enCad Walser Jean-Claude , 1 enCad Walser Jean-Claude , 1,2 P PadS ocie n eindtesuy P PadS rt the wrote SR and LP CP, study. the designed and conceived SR and LP CP, [email protected] encad.asreveh.h patri- [email protected]; [email protected]; 4 n Lo¨ıc Pellissier and , 3 arc Descombes Patrice , 2 arc Descombes Patrice , 1 5 2 hre oasd Santana de Novaes Charles , 3 hre oasde Novaes Charles , 1,2 Sergio , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. uniypatpliao neatosfo olnsmlsi h rnhCnrlPrne,wieIbanez while Pyrenees, Central French the of samples in many adaptation samples of the pollen collection through from the (Roslin facilitated interactions enables time been plant– which of has quantify sources, period Indian networks sample the short ecological in different a Island entire over to Heard of techniques on penguins study metabarcoding macaroni the DNA the opportunities then, of such regime Since opened trophic Ocean. the have reconstruct diffi- comprehensive, to the more protocol by barcoding and metabarcoding limited faster DNA been Novel cheaper, far locations. (Kaartinen increasingly so multiple are has at which (Pellissier gradients simultaneously documentation scale environmental interactions methods, the landscape comparable along to the observing networks at relate of ecological comparisons that culty network of networks perform the study ecological to The to of used 2018). study owing methods large-scale the studied, and networks the interactions poorly of to of challenges structure is gradients. major the networks climatic are in in along There changes variation networks to ecological geographic Morris lead multiple & the can documenting (Tylianakis Nevertheless, clines of co-occurring climatic 2015). difficulty steadily along Joern are shifts & to interactions they (Welti ability result, when their a even Pellissier and As species 2015; co-occurrence 2017). among species Joern interactions in & influence shifts (Welti might with links (Sentis associated stable temperature be form as can such gradients conditions, ecological are environmental composition, which in traits, variation functional Gounand by Laigle between 2014; influenced matching 2001; be of (Rausher might degree processes matching the co-evolutionary Laigle on 2010; depend through (Bascompte may shaped rules species ecological between by interactions governed rather of be (Barnes might but functioning compartments random hardly ecosystem how is understand between (Petchey us flow changes helps global networks matter by ecological negative disrupted and of and structure energy positive the for of studying webs 2018), species in among connected (Thompson interactions functioning are and and of processes ecosystems ecosystem of shape blocks which building interactions, main the ecosystems. represent of Species structure allows resili- the gradients on the ecological climate reinforce along of may networks Introduction influence that ecological the way Documenting of extinction. a understanding species in better alpine to wired a models. in ge- system are null species the of networks keystone in of plant–herbivore levels of than ence environments, importance in stronger reduced cold was increase and In correlation robustness an habitats. the greater plant–orthoptera found to and of We corresponded temperature, elevation. properties relationships decreasing These with structural with vary how nestedness standardized resilience examined and a we nerality and be- Using feces, specialization challenge. marginal to methodological reflecting remains a applied however, networks networks. is gradients, method interaction sites ecological species metabarcoding multiple and at of DNA interactions geographic rewiring species along structural camil- documenting structures with cause network associated Switzerland; of be Z¨urich, study to The 8092 expected are gradients 16, Universit¨atstrasse Ecological Z¨urich, ETH +41.44.632.23.45 Science, [email protected]; Systems vironmental author 2 Corresponding appendices: of number 1, tables: of Counts title running Short article of Type species. Keywords btat 4 od,mi et 27wrs ubro eeecs 1 ubro grs ,number 4, figures: of number 81, references: of number words, 5207 text: main words, 142 Abstract: tal. et N eaacdn,tohcntok ulmdl eeaiy outes etdes keystone nestedness, robustness, generality, model, null network, trophic metabarcoding, DNA tal. et 00 Roslin 2010; clg Letters Ecology 06,o yciai tblt (Dalsgaard stability climatic by or 2016), lvto n rpi ewr structure network trophic and Elevation ail itlu,Isiueo ersra csses eateto En- of Department Ecosystems, Terrestrial of Institute Pitteloud, Camille tal. et 09.Deagle 2019). tal. et tal. et 09.Frisac,Pornon instance, For 2019). 99 Tylianakis 1999; Abstract tal. et tal. et 2 20)wr mn h rtt eeo N meta- DNA a develop to first the among were (2007) 08.Mroe,sitn niomna conditions environmental shifting Moreover, 2018). tal. et tal. et 08.Tewrn mn neatn species interacting among wiring The 2008). tal. et 01.B nuigcagsi species in changes inducing By 2011). tal. et 08.I un ue ffunctional of rules turn, In 2018). tal. et 21)dvlpdapooo to protocol a developed (2016) 02.Gvntecnrlrole central the Given 2012). tal. et 08.Testrength The 2018). tal. et tal. et tal. et et Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. oe,weentok frnol itiue neatosaegnrtdadcmae ihteempirical the with compared and Several sizes generated links. different are interactions of possible distributed networks more randomly comparing of include of networks networks effects where confounding model, larger the as alleviate might Pellissier networks, to gradient (see to small developed the sensitive been of to indices have extremes structural large strategies the of from measures at affecting declines richness turn species inevitably in in richness, (Tr decline species size samp- the in matrix or as variation size significant regard, network in this of result effects in the challenging from is indices clines structural (Banaˇsek-Richter dif- network design on methodological patterns ling inherent interaction the real has (Pellissier of gradients comparison influence environmental network along of networks ficulties ecological of comparison The ihrpatseisrcns ol eetisc eeait ipyb nraigteaalblt fspecies of availability the increasing by simply that proposed generalists been (Unsicker has on benefit it feed diverse, could to less richness are species communities of plant plant capacity where of higher elevations, breadth the higher diet in larger at low a generality decline facilitate at herbivore a to expected (iii) is intense interactions, elevations higher 1967; plant–herbivore more (Pellissier at Levins to attack & (ii) herbivore (Macarthur linked the resist overlap 1967); closely niche to elevations Levins decrease more to higher & and, diets specialized (Macarthur at 2005); necessitates more conditions breadth Hodkinson for (i) these select diet to pattern: under survival predicted broader this is and elevations a 2008), support of (Barry Three predictable to evolution clines. less elevation the proposed be along to reshuffle been on expected may interactions is have McCann environment of resilience, hypotheses nodes 1973; network are in non-exclusive May which involved see main 1969), properties (Paine but structural (Power species 2017; general stability keystone robustness Morris of also system lower existence & the with the Tylianakis relies of associated 2009; result which be disturbances the Kuris to environmental is & found to This networks (Lafferty 2000). been the have extinction of networks species resilience Specialized against the 2010). quantify Fontaine also & can (Thebault structure network of Metrics hne nseis neatoswti ewrscnb umrzdb e fidctr eaigt the to relating indicators of set a by (Delmas network summarized (Bersier the be generality of of 1992), complexity can effect and networks the structuration within of of degree interactions evaluations species’ to in contributes Changes gradients stability. the elevation and in along structure networks links on species the temperature of of architecture Descombes turnover in the 2005; changes (Adedoja a with interactions in Hodkinson (ii) associated species 1995; or been of (Gravel (Rahbek networks has network, gradient elevation the the the increasing result and with in along a richness temperature interactions species as in species their the decrease change rewire steady can of the species gradients turnover particular, (O’Connor co-occurring environmental can a networks which along and (i) ecological in networks 2005) processes: network, ecological of main of Hodkinson structure two structure the 1995; of The over influence (Rahbek elevation 2015). vary to along communities Joern interactions expected – & in their temperature be filtering and notably also environmental most species therefore strong – montane how climate patterns, cause understand interaction in gradients to and Changes (K¨orner distribution laboratories 2003). gradients species natural environmental impacting optimal gradients natural represent of clines range study wide the the in while From advances gradients. bioinformatic to landscapes, spur environmental can entire and used along protocols, to techniques interactions lab user-friendly metabarcoding the and species wet DNA detailed of of the of as reproducibility workflows utilization of we- methodological and the all sharing description adaptability up also not complete the Scaling and interactions. limiting a scales, species accessible, addition, spatial document always large In not with resolution. is studies species-level procedures for at designed not aimed were re reconstruction network for protocols al. 21)apidti praht netfcsfrsuyn h ito nethrioe.Hwvr most However, herbivores. insect of diet the studying for feces insect to approach this applied (2013) tal. et tal. et ø esar lsn21;Pellissier 2016; Olesen & jelsgaard 02;Rasmann 2012a; 08frarve fteeapoce) h otcmol sdapoc stenull the is approach used commonly most The approaches). these of review a for 2018 tal. et tal. et 08 Welti 2008, tal. et 02,nsens (Bascompte nestedness 2002), tal. et 04.Suyn clgclntok ln ag-cl environmental large-scale along networks ecological Studying 2004). 04 Moreira 2014; tal. et tal. et tal. et 2017). tal. et 96.Teiprac n dniyo esoeseis but species, keystone of identity and importance The 1996). 08.Eetv nlsso ewr tutr slt the isolate structure network of analyses Effective 2018). tal. et 08 Pellissier 2018; tal. et 3 08.Frisac,tenme flnsprspecies per links of number the instance, For 2018). 08.I otatt h xetto fincreased of expectation the to contrast In 2018). tal. et tal. et 03 n outes(Dunne robustness and 2003) tal. et 09,icuigcnetne(Martinez connectance including 2019), 08.Teeoe tdigchanges studying Therefore, 2018). tal. et 07,lkl influencing likely 2017), tal. et tal. et 09 Welti 2009; tal. et 09.In 2019). 2002). Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. nrne(6 ftettlnme fsree pce) L n DCwr esrduigstandard using measured were elevati- LDMC their across and replicates SLA three species). of surveyed minimum of a number with total force species the well-developed, (LDMC), all of sampled content of We (76% matter traits (C/N). range dry ratio the October leaf carbon-to-nitrogen on measure and (from (SLA), to (punch), related site area leaves lamina that leaf each traits leaf healthy functional the specific at plant pierce content: ground measured regression to nutrient we the linear required species, or by plant in sites resistance keystone deep unmonitored physical the for study cm to To extrapolated 4 S3). was Fig. temperature buried S1, soil and (Appendix Summer Longville, 2018). capsule Newton October silicone HomeChip, to (DS1921G-F5 a 2017 0.5 loggers by a temperature protected at collec- using were parafilm, parameterized transect the data were per temperature performed sites Soil that We S2). the England) once. Fig. of S1, at half (Appendix all for gradient m elevation ted again the 100 them along the changed releasing within that species variable falcon before rare in m excretions, additional them fecal 9 for kept (Baur searched collecting a species, focused material for in per We plant plot individuals h, surveys times. living survey 10 2 vegetation on activity average m c. feed on peak 10 for caught to insect x known inspection, tubes were at visual are m surveys by that summer 10 orthoptera Orthopteran suborders the a identified grasslands vegetation. Ensifera during defined open and surrounding we conditions be the to weather site, on m chosen of each sunny 2417 were composition At to under Sites 578 activities. homogeneous conducted other. from each anthropogenic the elevations from from of spanning apart impact representative elevation sites, limited of eight bed- m into a information, 240 and divided (Supporting with average Salgesch climate was and on local transect Martigny located in Each Grindelwald, Faido, a.s.l., differing S1). Calanda, Alps, Fig. Bex, transects Swiss of S1, elevation areas the Appendix six the of established in conditions we i.e. environmental elevation, – of rock with diversity network the trophic covered plant–insect that the in variation study To collection data Field methods and Materials three following the proposed we Specifically, asso- environment. are alpine robustness plant–orthoptera increased the in and variation of organization structural temperatures network tran- the low hypotheses: of elevation explore the levels to six lower with models along if null ciated situated determine applied sites then and order We networks study in Alps. bipartite feces 48 Swiss orthopteran (Blumer across the to ecosystems networks applied in these metabarcoding sects bipartite of DNA functioning plant–orthoptera plant the for along reconstruct impact protocol networks to a strongly grass- optimized ecological they We semi-natural and plant–orthoptera 1996). in system, Diemer of Alpine & herbivorous structure European abundant the the most of the in lands among variation are the gradients Orthoptera investigated environmental gradients. elevation we along study, networks this comparing In when network variation the on size patterns matrix interaction 2003). observed of of Aizen (V´azquez role effect & the the isolate to from established structure been has method This patterns. I oegnrls nethrioe r rsn n h ewr smr outi odrenvironment, colder in robust more is network the and present are herbivores insect colder generalist in more higher If be 3. should primary plant simulated after network the of robustness The 2. according elevation) (higher environment colder in increase should orthoptera in generality of Levels 1. h eoa fpatseissol nuefwretntoswti rhpea omnte hnat than communities weights. orthopteran keystone within lower have extinctions plants fewer that induce so should elevation species low plant plant possible of for removal compensate the the better in to predicted communities behavior alpine feeding of generalist loss. networks insect species allow in should increase hypothesis dietary The first more elevations). offer high elevations (at higher higher environments for at found compensate typically to defences equipped . chemical specializa- for better plant for opportunities reduced are selection the positive feeders attenuates and generalist competition tion; argument: interspecific lower of uncertainty; lines environmental following the to 2 iclrpo oae ntems ooeeu oeo h 0 m 100 the of zone homogeneous most the in located plot circular ° eouinwt apigrt f20mnts rpe in wrapped minutes, 240 of rate sampling a with resolution C 2 4 lt eue eprtr stemi environmental main the as temperature used We plot. tal. et 2 06.We 2006). ltand plot Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. ewr fitrcin.W locluae h tnadzdeetsz SS oqatf h difference the quantify to randomized (SES) the for size obtained effect and slopes standardized temperature the the the of between calculated interval relationship also quantile of the We 2.5–97.5% significance of interactions. the Statistical slope networks. of outside observed observed network fell along the the variation metric if for metric network their confirmed applied and the to was as network variation according procedure each site metric same for (e.g. study the the properties calculation each following network metric for gradient, measured network reconstructed the further then of impossible We and were bias composition. randomized networks inherent fully species random were of interactions Individual where influence excluded. metawebs, the random links 999 from generated (packages We metric size). factor the network random on a interactions as random linear using identity tested nestedness transect were weighted metrics including lmerTest network the models observed computed the effects and finally for mixed temperature We randomly summer done ingested. mean of curve was not between removal proportion tolerance Relationships were species the attack that sequential and the Galeano taxa The removed under extinct. following plant species are area excluding of species the replicates, proportion all measures 100 until the It species, between (2007). insect relationship until surviving al. the species et plant describes in Burgos of which removal implemented by (ATC), sequential As introduced the extinct. robustness by are the caused (Dunne species extinctions networks weighted insect secondary species. the species all of of of orthopteran number proportion robustness per cumulative total The species the the intensities. plant by their divided of of (Bersier links number instead counts of mean marginal number the total the estimates the by which as package index, calculated R generality species, The the per links using of metrics we intensity number network step, interaction the final computed metrics of a We network estimate in In an variation low level. of with as species analyses OTUs sample the Statistical the each level, above out for assigned family filter (RRA) OTUs to the abundance surveys of above read (Deagle vegetation count relative identified used the the taxon, and/or section redistributed computed same S2, non-monophyletic and the Appendix 2019; were numbers, to in Team that read belonging procedures Core cleaning OTUs OTUs (R table the R reference discarded OTU summed using DNA We and networks After the bioinformatic 3). individual 2). against the reconstruct Methods assignment Methods of to section taxonomic database descriptions streamlined S2, and reference complete was Appendix calling the see table (see OTU expanded OTU species data, We plant the sequencing sites. the database, raw by priming of the the database 54% of and for reference processing generated primers ITS2 sequences the an custom between with compiled mismatch we one only sequencing, (Clark allow and Genbank preparation from database sequences reference library recovering the this (Li metabarcoding of selected coverage samples We DNA good DNA PCR. from resolution, degraded to amplicon is taxonomic extraction to the high sequencing, in application DNA amplification, amplified successful to after of was and short, extraction ease (360bp) its In marker DNA on plant 1. from based nuclear Methods marker metabarcoding ITS2 individually procedure, section the are wet-lab DNA feces, S2, samples the insect a Appendix which the of information, on in protocol Supporting approach relies full in PCR-based samples provided A amplification fecal dual-indexing. DNA by from two-step tagged a networks uses trophic that plant–insect procedure of reconstruction The elemental data an reconstruction trait using network of weight Plant–orthoptera collection (Kattge equal The datasets to Kingdom). published United pooled with Lancashire, replicates completed Wigan, intraspecific Instruments, was of CE from 0.2mg) (NC-2500 +/- analyzer (4mg material Sanson leaf following ground Japan), Toyohashi, LTD. CO., (P´erez-Harguindeguyprocedures tal. et untoae l 07.W sdanl oe praht iciiaeteeeto h non- the of effect the discriminate to approach model null a used We 2017). al. et Kuznetsova 09 Roslin 2019, tal. et 20) si a enascae ontokrbsns (Bascompte robustness network to associated been has it as (2009), tal. et 2019). tal. et tal. et 02 n scluae rmpeecsadasne finteractions of absences and presences from calculated is and 2002) 03.Pnhwscluae sn iia oc ag (IMADA gauge force digital a using calculated was Punch 2013). tal. et tal. et 06.Tedtbs a lee sn nslc Csthat PCRs in-silico using filtered was database The 2016). tal. et bipartite 5 01 K¨orner2011; bipartite 20) / a eemndb r obsinof combustion dry by determined was C/N (2001). tal. et h ucinue uniaieetmto of estimation quantitative a uses function the , 01 Garc´ıa-Robledo2011; (Dormann tal. et tal. et 06 Descombes 2016; 02,wihivle calculating involves which 2002), tal. et lme4 08.W osdrdthe considered We 2008). tal. et Bates 03.I parallel In 2013). tal. et tal. et tal. et 2017). 08and 2008 2003). 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Table slope 2, (observed Fig. models -3.51; = null and SES from nestedness -0.0060), different weighted (-0.0054, was the = between interval that network quantile SES relationship webs overall negative and 2.5–97.5% -3.44; empirical networks a 0.042, = S4a, random for found SES from Fig. further temperature -0.1868), observed obtained We (-0.4066, S1, the their slopes S1). = found (Appendix Table the interval we in quantile of elevation as interval 2.5–97.5% specialization the models, quantile (generality: null 2.5–97.5% high along from decreased were the (H2’) significantly values networks outside differed specialization be observed metrics network to these the slopes overall in of variation the generality The S1). of the -0.4973, Table that decrease = found a slope we (observed with hypothesis, temperature first increasing our with total individual 1. with The Fig. of agreement field. in reconstruction In illustrated the 6 The are in and links. transects metrics level genera three possible network taxonomic of 99 in 28,127 sites lower Variation species, of high-elevation a 496 and out to low- including 10,615 for identified taxa, was read exemplified not 601 networks recorded species of were of comprised interactions redistribution addition that table of equal the taxa OTU the number and to S2) the taxon, Appendix than same consumed, corresponding in higher the been families sections assignment to Results not taxonomic and belonging had a (Methods OTUs we that with ranks of 0.95, taxonomic OTUs merging lower of 176 to the assignment 15.5 and counts After of to monophyletic level. calling threshold not decreased OTU family stringent were after which a the OTUs that 1774 reads, used OTUs to that M and 105 identification reads, discarded 31 >36,500 taxonomic Salzberg of provided Following & depth 2016). run represented Magoc sequencing average genus (https://github.com/lh3/seqtk; families, (Edgar sequencing an their steps the with having PE trimming 2011), species of and 5969 Martin 2x300 missing merging 2011; 95.2% compiled the v3 paired-end of for database filtering, MiSeq 50% after surveys with reference The plantM species, vegetation barcoding database. the 496 the of DNA the of 88.5% of The in identification and suborders, diversity genera the families. Ensifera the taxonomic to 63 of and the 92.2% led and Caelifera covering surveys genera the sequences Vegetation of 265 reference samples. species to feces 16 belonging 403 and species, collected 29 we including and species, respectively, orthopteran 45 identified We reconstruction network and trait. surveys plant weightsField of We their space range. averaged functional elevation network, elevation the both each corresponding in For for them the Results scores sites. placed keystone elevation within and highest highest presence class the ade4 and elevation their with each lowest the on species for the from 10 based at the a.s.l.), dudi.pca species determined species m function plant further of (>2000 the of extracted traits elevation we score with plant high keystone classes, of traits and space the plant a.s.l.) functional and m on the (<1050 distribution analysis low the components the (Thioulouse examine The principal keystone package at To network. the a space as the species. performed functional hereafter in plant refer plant we taxa each we the plant which This for within of to extinct. removal, calculated number species became plant loss total then species by upon the insect was caused all extinct equaling extinctions score, until be n secondary removed to were with of the considered number species simulations, were for Plant mean n*(n–1) on. 2006), species source for feed Nepusz Insect food repeated they & species. was species a plant (Csardi plant providing of object the removal in all igraph random role of an and into major sequential transformed a a preliminarily to play network, that each taxa submitting plant scripts, as (Mills here herbivores defined orthopteran are species chance. Keystone by expected than species gradient keystone networks the empirical of the slopes of along Identification interactions suppress the variation the of not metric that interval the does indicate quantile SES) to here 2.5–97.5% of more the values used large contribute outside we (and values approach networks slope random The but from models. obtained effects, null sampling to the sensitivity and metrics’ relationships observed the between tal. et 08.W oprdtedsrbto fseiswt ieetkytn crsin scores keystone different with species of distribution the compared We 2018). tal. et 93 Power 1993; tal. et 6 96.W dnie esoeseisuigcso R custom using species keystone identified We 1996). P .3;Fg ,Tbe1 hc a consistent was which 1) Table 2, Fig. 0.035; = P = Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. Blig ony16) olradmr aibetmeaue ih lordc erhaddigestive and search reduce also might temperatures variable more elevations low and at increase Cooler than plants may 1968). host elevations Mooney the high of & variation reproduction at (Billings spatio-temporal and fluctuation greater developmental environmental into complete translates particular, which to stochasticity, In insects 1967; 2005). for Levins (Hodkinson constraints & cycles impose (Macarthur may defences chemical 2008) plant less Barry (K¨orner (ii) of 2003; predictability, relaxation environmental Rasmann (iii) lower 2005; and (i) Hodkinson resources, gradients: arguments elevation for underlying along competition three shifts with species species abiotic agrees of networks and architecture plant–orthoptera biotic alpine trophic stu- supporting for the our generality in understanding higher observed done for The as perspectives space, new in provide variation should network mo- time, of assemblages. and in monitoring specialized also the less but (Burgos enabling dy, are robustness methods environments network molecular cold Novel enhance 2014). in presumably (Dunne networks which nestedness that nested, and showing re connectance expectations network including theoretical between indices, support association on structural positive work and Theoretical a Memmott extinction space. 2002; suggests dis- functional increased, species networks homogeneous when species to ecological that plant more resilience of available argue a We relationship the through S1). over structure–stability Table presumably interaction of the S4a, herbivore resilience, spe- components Fig. network the central of S1, of higher be interactions levels Appendix tribution confer to 1; species reduced properties Table expected of displayed structural 4; theoretically environments rewiring Fig. these metrics 2, cold the are (Fig. high-elevation both which stability of of network nestedness, exhibited Networks result increased networks size. a and that network cialization showed as We in gradients, ecology’. shifts and the ‘landscape along of thus gradients, variation field elevation the structural along in sites (Nielsen multiple advances understan- networks across technical better networks interaction favoring plant–orthoptera a species of for structure of the way structure reconstructed the the paved shape has factors Roslin environmental methods how molecular of high-throughput ding novel of development The 3). (Fig. LDMC elevation SLA C/N, Forb low the of along at S2). Discussion distributed axes not Table mostly but opposing S1, were high the species (Appendix at keystone along family functional legume axis, space Poaceae keystone while trait the networks; three functional the high-elevation top occupied the to and The species low- in 3). belonged both keystone Fig. located all axis; 10 were environments this top species cold of extent keystone the and maximal environments, warm plant the for the of cold (to preferences of values and species punch space dietary warm high functional same by the both characterized had within top In space patterns networks The distribution 3). S2). trophic similar Table (Fig. lowland their S1, traits by and plant (Appendix illustrated single alpine extinction as a secondary from located groups, of removal insect sites botanical retrieved the one for with species than average sites low, keystones less on study generally in 0.26 10 were for average, (i.e. scores average keystone environments on on The colder resulting, S2). 0.41 in species Table (i.e. than S1, environments S2) Appendix Table warmer m; S1, >2000 in the Appendix scores for m; species <1050 not plant located but keystone traits 1) higher plant Table found S1). of Table We 2a, space S4c, (Fig. functional and networks the S4b empirical in Fig. species in between S1, Keystones relationship species (Appendix positive overlap per were a niche S1) 1), links found the Table Table We of S4c, or 2, networks. and number connectance (Fig. randomized S4b in the the Fig. species decrease and S1, and per the (Appendix observed temperature links attenuating orthoptera the of in of between number overlap interactions different niche the of not trophic in = wiring the Variation interval the and 2). quantile of connectance (Fig. (2.5–97.5% the role conditions models a colder nulls indicating toward from -5.77), robustness expected = than SES lower 0.0082), was (0.0057, environments 0.0033, = cold (slope in temperature robustness and robustness between relationship tal. et 09.Uiga mrvdadnnivsv eaacdn rcdr ae nisc ee,we feces, insect on based procedure metabarcoding non-invasive and improved an Using 2019). tal. et 04 aet ui 09.Oreprclaaye ln eea lvto transects elevation several along analyses empirical Our 2009). Kuris & Lafferty 2004; tal. et 04.Frt rae niomna tessadvraini h liebelt alpine the in variation and stresses environmental greater First, 2014). 7 P tal. et .2) u h bevddces in decrease observed the but 0.023), = 07 ilrSrtmn Galen & Miller-Struttmann 2007; vs tal. et L in SLA . tal. et 2018; Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. 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Table might proper Galen 2c, hyper-generalists on a (Fig. those feeding elevation with of generalist, with often presence extreme nestedness more The were of 4). elevation increase (Fig. higher reported communities (Appendix at high the the species to orthoptera in at some lower-elevation species that growing plant of Boraginaceae, found all Apiaceae, we plants habits almost as particular, feeding such in In families the S7). intensively levels Fig. more with S1, target defence compared and Fabaceae, in families plant and reduction of Caryophyllaceae range generalized broader digestibility a a on easier feed with through agreement environments, (Rasmann in colder elevations are in plants behavior low- (Moreira alpine than feeding materials herbivores plant generalist to Table various resistant stronger S4c, of less a Fig. are S1, promote communities plant (Appendix could alpine (Rasmann orthoptera that communities indicating in shown gradient, plant weakened previously temperature elevation is was the resources along it no vary plant Third, S1, not found S1). for (Appendix did we specialization orthoptera competition However, network among interspecific 2005). overall overlap that the niche Hodkinson and species 1967; 1981) orthoptera and Levins focusing of S6) of (Cates by & richness Fig. richness competition (Macarthur breadth species species escape diets the to diet higher between specialized species Second, large relationship pressure more generality. might a and in S5) plant maintaining Fig. distinct increase the S1, observed on by food (Appendix the as elevations species while low to such plant at Hence, contribute orthoptera clades, could food 26). factors specialized of was other more fluctuations Pellissier study and plants, of demographic our host the specialization in orthoptera eight for plants evolutionary Overall, of host the 1967). (median of impact Levins butterflies number largely & median (Macarthur should (the behavior fluctuation feeders feeding offset generalist generalist be could of are unpredictably environmental reinforcement such turn, the In 2005). through (Hodkinson ectothermic in efficiency 03) efudlwradmr vnkytn crsfrapn ln pce,maigta h removal the that meaning species, plant alpine for scores keystone even more and lower found We 2013a). 03,poiighrioe ihhge urtv otn uigtesotgoigsao ftealpine the of season growing short the during content nutritive higher with herbivores providing 2013), tal. et tal. et tal. et 09.Teascainbtenntokseilzto,nsens n robustness and nestedness specialization, network between association The 2019). 21)as hwdhge etdesa euto rvlneo super-generalist of prevalence a of result a as nestedness higher showed also (2019) 04.W ouetdta rhpea omnte rmcl environments cold from communities orthopteran that documented We 2014). tal. et tal. et 08.Orrslsidctn oe eetvns fototr for orthoptera of selectiveness lower indicating results Our 2018). 04 Callis-Duehl 2014; tal. et 8 02) rhpeamgtmr aiycompensate easily more might orthoptera 2012b), tal. et 07.Teepatdfnepatterns defence plant These 2017). tal. et rms Festuca Bromus, 03 ilrSrtmn & Miller-Struttmann 2003; tal. et 07 rnested- or 2017) and Nardus et et Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. ans .. ohm . ecek .. iehur . cebr . ’onr M.I., functioning. O’Connor, ecosystem C., and Scherber, N., multitrophic between Eisenhauer, 186–197. link 33, J.S., The Lefcheck, flux: M., Energy Jochum, A.D., quantitative Barnes, of robustness the descriptors. and effects food-web Sampling qualitative (2004). and L.F. Bersier, & networks. M.F. plant-herbivore Banaˇsek-Richter, Cattin, of C., robustness and structure the in Biogeogr. patterns Global (2016). endemic de. Ara´ujo, among W.S. gradient. vary elevation networks interaction an Insect-flower over (2018). taxa M.J. Samways, pollinator & T. for Kehinde, Fund O.A., Adedoja, Swiss Guisan). National Antoine the to by 31003A-125145 funded SR, was to References work 31003A_179481 Daniele LP, This to Salamin. Dettling, 162604 Nicolas Gabriel (grants and Albouy, research Guisan Camille Pradervand, Antoine Marie- Jean-Nicolas to Litsios, Reymond, Abella, in also Alain Glenn Ang´eline Casanelles Zurich, Bollenbach, Bedolla, Joan sampling. Thanks in Janka Fopp, field ETH Lanfranchi, used Fabian Sandau. in Marco Donati, data at help Pezzotta, Nadine invaluable Giulia the their (GDC) thank Baetz, analyzing for we and Nico Centre Poirier collection, Maude Ang`ele producing Pitteloud, Diversity data and in in Roesti Genetic assistance assistance Christian their their to the For thanks for at special Minder A Aria collaborators paper. and this our Kobel Silvia to to grateful particular deeply are We interest. of conflict no Acknowledgements have they that declare authors The (Chist´e interest orthoptera extinction. underlying of assemblages in factors species species Conflict eco-evolutionary of extinctions resilient the rate how to of highlights accelerated lead also understanding the but better to then gradients, a are ecological could to large-scale way which along the regularly structure species, paving can network plant fertilizers, helps of study multiple use Our land of the the 2016). of through intensification that loss instance Nevertheless, in the for extinctions. extinction, grasslands, secondary cause to mountain cause sensitive lower-elevation to very in necessary not practices is use are species orthoptera plant Generally, multiple possibility. of would investigation this the loss further responses confirm although entangled alter to defences, represent required chemical suggest can elevation plant We be by regarding and pressures. components predictability variation 2017), biotic environmental structural and Morris abiotic to network networks abiotic & of of in both Tylianakis through patterns 2015; Shifts interface observed Joern species the environments. the & that of (Welti lowland with aspects indirectly in different nestedness or the directly weights than influencing and lower interactions gives generality alpine species ultimately network of in and structuring gradient plant–herbivore species the in along keystone robustness increase network in to in an variation variation show drives spatio-temporal data. which results possible elevation, interaction the our species collecting on together, for investigation Taken (Mata means of here the fields assessed expanding not open by were may interactions sampling composition plant–insect approach of diet impacts our compromise on potential Overall, change a resources, year-to-year sampling 2019). As available and species. the seasonality and insect and study and our replication plants of involving coverage spatial interactions docu- the documenting literature-based between or for content method gut adaptable or feces easily of and (Nielsen analyses mechanical interactions visual of on from mentation based resulting methods traditional presumably with Compared defence, plant and tradeoffs. ability defence feeding chemical insect between mechanisms 8. , tal. et .Ter Biol. Theor. J. 08,teDAmtbroigpoeuerpeet neetv and effective an represents procedure metabarcoding DNA the 2018), LSOne PLoS 9 3 e0207453. 13, , 2,23–32. 226, , rnsEo.Evol. Ecol. Trends tal. et (2018). Front. tal. et tal. et , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. omn,C,Gue,B rud .(08.Itouigtebpriepcae nlsn clgclnet- ecological analysing package: bipartite the Introducing (2008). Fr¨und, J. & B. works. Gruber, declines. C., abundance herbivore Dormann, insect as S., elevation Rasmann, with A., increases Guisan, palatability J., plant Bilat, level Jn.N., Pradervand, M.-J., J., Fortin, Marchon, P., V., Descombes, G. Riva, interactions. Dalla species L.A., data? of Burkle, networks dietary M.-H., ecological Brice, to M., reads Besson, sequence E., convert Delmas, we should How studies: 391–406. E.L., 28, Clare, metabarcoding E.J., Vesterinen, in L.J., DNA Clarke, chrysolophus). J.C., with (Eudyptes McInnes, penguins A.C., Thomas, macaroni B.E., on Deagle, study case A faeces: R., Trebilco, of One S., analysis Robinson, genetic S.N., Jarman, through K., diet Evans, N.J., Gales, B.E., Deagle, precipitation contemporary velocity. richness, climate-change species J.M., quaternary with Olesen, and associated is C., research. networks plant-hummingbird network Rahbek, in Specialization complex Mart´ın Gonz´alez, A.M., Fjelds˚a, Mag˚ard, for J., E., package B., software Dalsgaard, igraph The (2006). T. Syst. Complex Nepusz, & G. GenBank. (2016). Csardi, E.W. Sayers, & J. 67–72. Ostell, 44, D.J., , Lipman, I., Karsch-mizrachi, K., Clark, communities. orthopteran W.W., affects intensity Weisser, land-use K¨ohler, G., grassland e01545. N.K., How Simons, opportunists: and M.M., and oligophagous, winners, Gossner, monophagous, plant K., of of Mody, patterns Chist´e, feeding M.N., relaxation the Community-level and predictability herbivores. plant (2017). insect Host polyphagous S. (1981). Rasmann, R.G. & Cates, elevation. E. high M., at Defossez, herbivores Zimmermann, P., against D., defenses Vittoz, Medan, K., M., Callis-Duehl, Devoto, alpine R.P.J., an networks? in Perazzo, mutualistic herbivory in H., nestedness Ceva, of consequences E., and Burgos, occurrence The plants. Alps. alpine central (1996). and Swiss M. arctic grassland, Diemer, of & ecology P. The Blumer, (1968). H.A. Mooney, matrices. & food-web W.D. of Billings, descriptors Quantitative (2002). M.-F. Cattin, Ecology & (2006). Banaˇsek-Richter, C. D. L.-F., Roesti, Bersier, & C. Roesti, Package H., lme4 Baur, plant- the B., using of Baur, models assembly mixed-effects Fitting nested (2008). S. The R. Walker, in & (2003). B. Bolker, M¨achler, J.M. M., D., Olesen, Bates, & Meli´an, C.J. P., networks. mutualistic Jordano, networks. ecological J., of Bascompte, dynamics and Structure (2010). J. Bascompte, Cambridge. Press, (2008). R.G. Barry, ,e831. 2, , .Sa.Softw. Stat. J. news R 3 2394–2407. 83, , 65 1–9. 1695, , ,8–11. 8, , 67. , onanwahradclimate and weather Mountain rc al cd c.U .A. S. U. Sci. Acad. Natl. Proc. rt l.Res. Alp. Arct. Oecologia .Ter Biol. Theor. J. LSOne PLoS 8 319–326. 48, , il Rev. Biol. 8 435. 28, , ln Ecol. Plant atrle,Giln tCiut eSuisse de Criquets et Grillons Sauterelles, ,e25891. 6, , 10 4,307–313. 249, , . 4 16–36. 94, , 0,9383–9387. 100, , t ete Clim. Weather Mt. 1,291–304. 218, , Science r d.CmrdeUniversity Cambridge edn. 3rd tal. et 2,765–6. 329, , il Rev. Biol. tal. et 20) tdigseabird Studying (2007). tal. et .Ecol. J. tal. et tal. et tal. et 21) Community- (2017). uli cd Res. Acids Nucleic 21) Analysing (2019). 21) Counting (2019). 3 481–529. 43, , 21) Losers, (2016). 0,142–151. 105, , ap,Bern. Haupt, . Ecosphere 20) Why (2007). tal. et InterJournal o.Ecol. Mol. (2011). PLoS 7, , , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. ao,T azeg ..(01.FAH atlnt duteto hr ed oipoegenome improve to reads short of adjustment length fast FLASH: (2011). S.L. Salzberg, assemblies. & T. species. coexisting Magoc, of divergence and convergence, similarity, barcode limiting core The Nat. (1967). the Am. R. into Levins, incorporated & J.-Q., R. be Macarthur, Liu, should X.-J., (ITS) spacer Ge, plants. transcribed H., seed internal Wang, food for that of H.-T., indicates drivers Li, as dataset traits L.-M., large Species Gao, (2018). D. D.-Z., Gravel, Li, & I. Boulangeat, to U., Brose, sensitive structure. C., are web Digel, I., they Aubin, because I., Laigle, robustness snail. web estuarine invasive food an reduce by Parasites 1659–1663. illustrated (2009). as A.M. extinction secondary Kuris, & effects K.D. mixed Lafferty, linear in tests package: lmerTest (2017). isotope R.H.B. stable models. samples. Christensen, nitrogen & herbarium P.B. and on Brockhoff, Carbon A., based Kuznetsova, (2016). flora, L. alpine Streule, entire & an R.T. for Siegwolf, signals S., Riedl, S., Leuzinger, K¨orner, C., Berlin. Springer, (2003). K¨orner, C. barco- traits. B¨onisch, DNA P., plant G., Leadley, liaisons: of I.C., secret Prentice, Revealing S., Lavorel, D´ıaz, (2010). S., J., webs. T. Kattge, Roslin, food & of K. understanding Lohse, our . J., changes of Hearn, ding diet G.N., the Stone, to R., preferences Kaartinen, food and 1459–1470. S., of 173, Aubert, contribution , A., relative Valentini, P., the Taberlet, biome- reveal C., between traits Miquel, coupling O., by Manneville, mediated S., Herbivory Ibanez, grasshoppers. (2013a). and M. plants Moretti, to of & S. traits responses Puijalon, chanical community S., Lavorel, and S., species Ibanez, gradients: interaction elevation ecological along of insects Terrestrial altitude. (2005). the I.D. represent Hodkinson, to framework quantitative T., Nyman, a N.D., networks. together: Martinez, J.-P., roles Grinnell Kopelke, the J.A., and assembly: Dunne, web B., food Baiser, D., during Gravel, selection Trait (2016). temperature. D. and Gravel, interactions & of N. Mouquet, K´efi, S., I., barcodes. Gounand, DNA plant-herbivore using Tropical interactions (2013). W.J. species Kress, reconstructing & networks: T.L. Erwin, C.L., new Staines, a D.L., (WINE): Garc´ıa-Robledo, Erickson, matrices. estimator C., nestedness frequency Weighted-interaction over (2009). sequencing. calculate J.M. to amplicon Iriondo, estimator & ITS J.M. and Pastor, J., 16S Galeano, Illumina for error-correction improved webs: food UNOISE2: bioRxiv in (2016). loss R.C. biodiversity and Edgar, structure Network connectance. (2002). N.D. with Martinez, increases & robustness R.J. Williams, J.A., Dunne, .Sa.Softw. Stat. J. 81257. , il Rev. Biol. 0,377–385. 101, , cgah (Cop.). Ecography Bioinformatics Oikos lb hn.Biol. Chang. Glob. rc al cd c.U .A. S. U. Sci. Acad. Natl. Proc. h liepatlf:fntoa ln clg fhg onanecosystems mountain high of ecology plant functional life: plant alpine The 0 489. 80, , 2,316–326. 127, , 83. , 7 2957–2963. 27, , 2 401–415. 42, , ho.Ecol. Theor. 7 2905–2935. 17, , cl Lett. Ecol. uc.Ecol. Funct. ,417–429. 9, , cl Entomol. Ecol. nio.Mdl Softw. Model. Environ. 0,19641–6. 108, , ,558–567. 5, , 11 7 479–489. 27, , 5 623–638. 35, , l.Bot. Alp. hls rn.R o.BBo.Sci. Biol. B Soc. R. Trans. Philos. tal. et LSOne PLoS tal. et 4 1342–1346. 24, , 2,153–166. 126, , 21) oprtv nlsso a of analysis Comparative (2011). 21) R lbldatabase global a - TRY (2011). tal. et 8. , tal. et 21b.Patfunctional Plant (2013b). 21) rnigElton Bringing (2019). n edn. 2nd . Oecologia 364, , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. abk .(95.Teeeainlgain fseisrcns:auiompattern? uniform a richness: species of gradient elevational 200–205. The Statistical for (1995). Foundation C. R Rahbek, computing. statistical https://www.r-project.org/. for URL environment and Austria. language Vienna, A Computing, R: (2019). Team. L.S., Core Mills, R W.J., Bond, B.A., Keystones. Menge, J.A., for Estes, Quest J., D., Mariette, Tilman, M.E., A., interactions. Power, Khimoun, plant-pollinator quantify H., and Holota, reveal M., to Burrus, barcoding N., Escaravage, A., Pornon, food-web alters warming Environmental function. (1999). ecosystem P.J. and Morin, & structure T.M. worldwide. Casey, P.T., traits McPhearson, functional O.L., Petchey, plant of measurement P., Jaureguiberry, standardised H., for Poorter, handbook ? J., S., ant-caterpillar Lavorel, Pottier, E., of A., Garnier, evolution D´ıaz,P´erez-Harguindeguy, Dubuis, S., the N., K., for Fiedler, prerequisite G., A content: Litsios, nitrogen S., gradients. Rasmann, elevation L., along Pellissier, resistance A., plant Guisan, and J.N., Pradervand, specialization, M., A., herbivore Dubuis, Loreau, richness, C., Ndribe, C., K., Fiedler, Graham, L., Pellissier, N., gradients. Farwig, environmental J., along networks Bascompte, interaction stability. C., species community Albouy, and complexity L., trophic Pellissier, on availa- note resource A and Warming (1969). (2009). R.T. metabolism. J.F. Paine, and Method Bruno, structure & ecology: web A. in Anton, food tracing D.M., shift Diet Leech, bility (2018). M.F., P. Piehler, M.I., Kratina, O’Connor, & M.T. Brett, selection. B., and Hayden, comparison research. E.L., future Clare, for J.M., prospects Nielsen, and field in the gradients Elevational in advances (2018). recent L. (Cop.). herbivory: Abdala-Roberts, insect & and S. Rasmann, defences Conservation. K.A., plant Mooney, and W.K., Ecology Petry, X., in Moreira, Concept Keystone-Species The (1993). D.F. Bioscience Doak, & Soul´e, M.E. L.S., broadens Mills, use plant gradient. food bee extinctions. bumble altitudinal multi-taskers: species an High-altitude to (2014). along C. networks Galen, & of N.E. Miller-Struttmann, Tolerance Sci. (2004). Biol. V. B M. Soc. Price, R. & Proc. N.M. Waser, J., Memmott, debate. diversity-stability The (2000). K.S. McCann, ecosystems. Biol. model Popul. enough? in Monogr. is complexity much analysis. and How Stability dietary (2019). P. (1973). metabarcoding Beja, R.M. on May, & replication S. biological Jarman, and G.F., technical McCracken, of F., Amorim, Effects H., webs. Rebelo, food V.A., community Mata, in reads. connectance sequencing Constant high-throughput (1992). N.D. from Martinez, sequences adapter removes Cutadapt net.journal (2011). M. Martin, 1 1485–1496. 41, , 3 219–224. 43, , 7 10. 17, , Bioscience ehd cl Evol. Ecol. Methods 7,2605–2611. 271, , 6 609–620. 46, , Nature 0,69–72. 402, , Oecologia ,278–291. 9, , LSBiol. PLoS 12 7,1033–1045. 176, , Nature ,e1000178. 7, , il Rev. Biol. 0,228–233. 405, , c.Rep. Sci. 3 785–800. 93, , m Nat. Am. ,27282. 6, , m Nat. Am. tal. et tal. et tal. et ut .Bot. J. Aust. .Eo.Biol. Evol. J. cl Evol. Ecol. tal. et o.Ecol. Mol. 3,1208–1218. 139, , tal. et 19) hlegsi the in Challenges (1996). 21b.Hg host-plant High (2012b). 21a.Sit nspecies in Shifts (2012a). cgah (Cop.). Ecography 0,91–93. 103, , 21) sn meta- Using (2016). 21) Comparing (2018). tal. et ,1818–1825. 2, , 1 167–234. 61, , 8 165–175. 28, , 21) New (2013). Ecography EMB- 18, , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. ie(E)maue ewe h bevdmti lpsadtoeotie rmrno ewrsof networks random are networks from random for obtained obtained those slopes the and of temperature, limits slopes the interval quantile metric and 97.5% metric observed and observed 2.5% the the the between and between interactions, measured relationship (SES) the of the size estimate, slope intercept the the metric, each For models. 1 climate Table and grazing Fire, (2019). A. prairie. Joern, Tables & tallgrass J. a Blair, in M., interactions Ungerer, plant–grasshopper H.M., shape Tetreault, environmental F., broad Qiu, across E.A.R., networks plant- Welti, mutualistic and and communities trophic of Structure on (2015). gradients. diversity A. Joern, plant & of E.A.R. Impacts Welti, (2017). A. Joern, architecture. network & herbivore C. interactions. Helzer, plant-pollinator E., in Welti, specialization of analyses model Null dietary Ecology (2003). herbivore. through M.A. insect effects Aizen, generalist Complementarity & V´azquez, a D.P. (2008). of W.W. performance Weisser, the & enhance K¨ohler, gradients. G. mixing A., environmental Oswald, across S.B., networks Unsicker, Ecological (2017). Syst. R.J. Evol. Morris, Ecol. & J.M. interactionsTylianakis, species and change Global (2008). ecosystems. D.A. terrestrial Wardle, & in J. Bascompte, R.K., Didham, J.M., Tylianakis, scales. across R.L., Kitching, S., biodiversity. (2018). Tr Hladyz, of S. function R.O., and Hall, Pavoine, structure J.A., & the Dunne, reconciling A. U., Brose, Siberchicot, R.M., S., Thompson, Dray, ade4 T., with data Jombart, ecological mutualistic of A.B., of analysis architecture Dufour, the J., and Thioulouse, communities ecological of Stability networks. (2010). temperature trophic C. and of Fontaine, structure. & understanding food-web E. mechanistic and Thebault, a omnivory Towards strength, (2014). interaction biomechanical species J. 785–793. leaf on Brodeur, of effects & Measurement enrichment J.L. (2001). and P. procedures. Hemptinne, and Peeters, A., problems & Sentis, Opportunities, F. herbivory: network Clissold, of shapes N., studies Aranwela, introduction in properties J., species Experimental Read, (2019). G., K. Sanson, Shea, community. & plant-pollinator C. a Campbell, in interactions R., Introduction: Albert, (2019). L., W.O.C. Russo, entangled Symondson, the Untangling & techniques. – S. dynamics molecular community Creer, and using networks G.N., bank ecological interactions, Stone, species M., on issue Jonsson, Special enemies. M., natural plant Traugott, to T., insect resistance Roslin, in plant hypothesis and Co-evolution niche-breadth (2001). altitudinal M.D. The Rausher, (2014). L. Pellissier, & interactions. N. Alvarez, S., Rasmann, ø esar,K lsn ..(06.Eooia ewrsi oin ir-admcocpcvariability macroscopic and micro- motion: in networks Ecological (2016). J.M. Olesen, & K. jelsgaard, 4 2493–2501. 84, , offiinsotie o h bevdmti aito ln h eprtr rdetadtenull the and gradient temperature the along variation metric observed the for obtained Coefficients cl Evol. Ecol. n.PatRev Plant Ann. uc.Ecol. Funct. 8 annurev-ecolsys-110316-022821. 48, , Science ,326–334. 5, , cl Lett. Ecol. 0 1926–1935. 30, , p 7 339–360. 47, , 2,853–856. 329, , au ( value Ecosphere o.Ecol. Mol. 1 1351–1363. 11, , . P utvr nl cl aawt ade4 with Data Ecol. Anal. Multivar. ,tedgeso reo d) h -au,tesadrie effect standardized the t-value, the (df), freedom of degrees the ), ,e01983. 8, , 8 157–164. 28, , il Invasions Biol. 13 rnsEo.Evol. Ecol. Trends uc.Ecol. Funct. 1 3505–3519. 21, , Oecologia 3 735–745. 33, , 7 689–697. 27, , pigrNwYr,NwYork. New York, New Springer . 5,313–324. 156, , uta Ecol. Austral Nature tal. et 1,857–864. 411, , 21) odwebs: Food (2012). 6 535–546. 26, , cl Lett. Ecol. Multivariate nu Rev. Annu. 17, , Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. hpea n ln pce.Itrcinitniyi niae yteclrgain ihdr lecorre- blue or- dark to with respectively gradient absence. color correspond interaction the to rows by white and and indicated strength Columns is interaction intensity maximal Interaction transects. to sponding elevation species. plant the three and of along thopteran axes found first two sites corner. the elevation right and top high). 4 and the SLA) medium in and Figure of (low, plot punch sizes secondary number the circle 0.75 LDMC, mean in three and (C/N, the given as 0.12 are traits to legend between PCA the varies functional corresponds in It plant 0.0082 score taxonomic summarized between keystone plant species. is by plant Correlations The but first colored the networks explain black. are of all the removal which across species in onto the extinctions keystone traits, shown by 10 projected are functional caused top are plant species extinctions The secondary on other species variance. -0.1868 all Plant performed the of while (PCA) (PC2) communities. group, analysis 15.6% plant components and m) principal (PC1) 0.0057 58.8% >2000 the (b, of 0.0060 high-elevation axes -5.77 two and observed from the obtained when a.s.l.) models. slopes grey m null dark the from are -0.4066 expected of they 3 interval interval while Figure slope 2.06 0.1032 red, quantile the -3.44 are 2.5–97.5% outside values not the metric 43.62 is and outside line slope -0.0054 in is significant regression temperature a the relationship represented 0.023 the networks, networks, indicate empirical are of random -3.51 empirical -2.17 lines For the line models solid temperature. of regression null where the slope and 43.66 and on models, interval metrics effects based network confidence mixed random metrics the 0.035 or linear 0.0816 -2.10 observed Expected from the weighted result between (b), relationship lines (d). -1.82 generality 43.91 network Regression robustness (a), gray. network species light insect 0.042 per and intensity. the and links interaction of (c), of plant represents taxa number nestedness links of the metrics: the 3.20 to network reconstruction of plant–orthoptera correspond width The various label The no 42.56 right. name. with 2 to Bars Figure genus 0.74 left (e.g. from the Methods. 0.003 reading genera section following bar, S1, non-monophyletic number labelled Appendix plants, to preceding a for in belonging families with detailed 36.28 To into species is indicated and plant. 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Data may be preliminary. i.4 Fig. plant-herbivore-ecological-networks-varies-along-elevation-gradients image4.emf file Hosted 3 Fig. plant-herbivore-ecological-networks-varies-along-elevation-gradients image3.emf file Hosted 2 Fig. plant-herbivore-ecological-networks-varies-along-elevation-gradients image2.emf file Hosted 1 Fig. vial at available at available at available https://authorea.com/users/317969/articles/447994-the-structure-of- https://authorea.com/users/317969/articles/447994-the-structure-of- https://authorea.com/users/317969/articles/447994-the-structure-of- 15 Posted on Authorea 6 May 2020 | CC BY 4.0 | https://doi.org/10.22541/au.158880251.12111301 | This a preprint and has not been peer reviewed. Data may be preliminary. C F G a a r i i l nde do enda

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