Proportion of non-native plants in urban parks correlates with climate, socioeconomic factors and plant traits

U ban Fo es y & U ban G eening 63 (2021) 127215 A ailable online 12 June 2021 1618-8667/© 2021 Published by Else ie GmbH. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/). P opo ion o non-na i e plan s in u ban pa ks co ela es wi h clima e, socioeconomic ac o s and plan ai s ´ Al a o Bay´ on a , Osca Godoy b , No¨ elie Mau el c , Ma k an Kleunen c , d , Mon se a Vil` a a , e , * a Es aci´ on Biol´ ogica de Do˜ nana (EBD-CSIC), A . Am´ e ico Vespucio 26, 41092, Se illa, Spain b Depa men o Biology, Uni e si y o Cadiz, Cadiz, Spain c Ecology, Depa men o Biology, Uni e si y o Kons anz, Kons anz, Ge many d Zhejiang P o incial Key Labo a o y o Plan E olu iona y Ecology and Conse a ion, Taizhou Uni e si y, Taizhou, 318000, China e Depa men o Plan Biology and Ecology, Uni e si y o Se ille, Se ille, Spain ARTICLE INFO Handling Edi o : W Wendy McWilliam Keywo ds: Ha diness zones In asi e species O namen al plan s Plan ai p o ile ABSTRACT U ban pa ks and ga dens p o ide cul u al and aes he ic se ices c i ical o human well-being. Ye , hey ep esen one o he main easons o he in en ional in oduc ion o o namen al species, some o which can escape and es ablish in na u al ecosys ems. Besides aes he ic easons, clima e and socioeconomic ac o s can also modula e which species a e plan ed in u ban pa ks. He e, we e alua e he ela ionship be ween ai s o 486 o namen al woody species om 46 Spanish u ban pa ks and clima ic and socioeconomic a iables. We speci - ically assessed how plan ai s, clima ic, and socioeconomic ac o s a e ela ed o he p opo ion o non-na i e species and, among hem, o he p opo ion o es ablished non-na i e species in Spain. O e all, we ound clea associa ions be ween species ai s and clima ic a iables. Mos no ably, pa ks wi h wa me win e s ha e mo e plan species wi h conspicuous lowe s, whe eas pa ks wi h colde win e s and a mo e con inen al clima e ha e mo e species wi h highe ole ances o cold and shade. Mos o he species eco ded in ou s udy a e non-na i e (82 %). Highe p opo ions o non-na i e species in u ban pa ks we e posi i ely associa ed wi h owns wi h la ge size homes and inhabi an s wi h highe median age bu nega i ely ela ed o pa ks wi h species wi h a highe ha diness-zone ange. Mo eo e , a g ea e p opo ion o non-na i e species ha can es ablish in he na u al ecosys ems was ound in pa ks wi h lowe con inen ali y condi ions. Ou esul s show ha Spanish u ban pa ks ha e an o e whelming p opo ion o non-na i e woody species, some o which ha e he po en ial o es ablish, and ha he a ia ion in hei p opo ions can be explained by clima ic, and socioeconomic ac o s. 1. In oduc ion U ban pa ks and ga dens p o ide cul u al and aes he ic se ices c i ical o human well-being (Bolund and Hunhamma , 1999; Hulme, 2007; Kendal e al., 2012), ye hey a e one o he main easons o he in en ional in oduc ion o o namen al non-na i e plan species wo ld- wide (Maye e al., 2017; an Kleunen e al., 2018). This sou ce o non-na i e species in oduc ion is pa ly explained by he ac ha in ou con inuous sea ch o no el y, we, as humans, a e ac i ely looking o plan ea u es ha inc ease he aes he ic alue o u ban pa ks while c ea ing a sense o place. In addi ion, p e ious wo k has shown ha such sea ch is also modula ed by he socioeconomic con ex o he owns wi hin a coun y. In gene al, he p esence o non-na i e plan species is explained by clima e, human ac o s and a combina ion o bo h (Pyˇ sek e al., 2010). Fo ins ance, owns wi h high a e age incomes and high de elopmen dedica e g ea e mone a y in es men o he in oduc ion o no el species wi h highe aes he ic alue (Vaz e al., 2018) and o he main enance o g een a eas, wi h mo e di e se species composi ion (Pyˇ sek e al., 2010). Likewise, densely popula ed egions a e cha ac- e ized by highe p opagule p essu e, he e o e, mo e indi iduals a e plan ed and mo e in asi e plan s p esen (Pino e al., 2005; Pyˇ sek e al., 2010). Ne e heless, he deco a i e alue is only one eason o plan ing non-na i e species in u ban pa k. O he impo an easons ela e o he abili y o some non-na i e species o cope wi h en i onmen al s ess. Commonly, pa k manage s selec species ha a e easy o es ablish and main ain. This means inding species wi h pa icula ai s ha a e p e- adap ed o he pa icula clima ic condi ions. Howe e , his * Co esponding au ho . E-mail add esses: [email p o ec ed] (´ A. Bay´ on), [email p o ec ed] (M. Vil` a). Con en s lis s a ailable a ScienceDi ec U ban Fo es y & U ban G eening jou nal homepage: www.else ie .com/loca e/u ug h ps://doi.o g/10.1016/j.u ug.2021.127215 Recei ed 30 No embe 2020; Recei ed in e ised o m 2 June 2021; Accep ed 7 June 2021 U ban Fo es y & U ban G eening 63 (2021) 127215 2 managemen can b ing en i onmen al p oblems as i also acili a es hei es ablishmen in na u al ecosys ems in he in oduced ange (Gonz´ alez-Mo eno e al., 2014; Mau el e al., 2016; Pyˇ sek e al., 2010). In gene al e ms, i has been well-documen ed ha he dis ibu ion o woody species along clima ic g adien s is modula ed by he pa icula o gans and whole-plan ai s ha allow species o ole a e en i on- men al s esso s such as os , shade, and d ough (Rueda e al., 2017; Zanne e al., 2014). The e o e, when a non-na i e species is in oduced in a no el a ea, he in e ac ion o clima ic condi ions wi h he species ai s de e mine which species will pe sis (Haeuse e al., 2018, 2017; Dullinge e al., 2017; an de Veken e al., 2008). This in e ac i e p ocess is no di e en in he case o u ban lo as, al hough ga dening p ac ices (e.g. wa e ing, d ainage sys ems o excess wa e , p uning) can o e come o compensa e o some o hese clima ic limi a ions. The in oduc ion o non-na i e woody species in u ban pa ks can pose a conse a ion p oblem because some o he species can escape, es ablish popula ions (i.e. na u alize) in na u al ecosys ems and become in asi e. Se e al in asi e woody species ha e he po en ial o dis up he unc ioning o na u al ecosys ems causing en i onmen al impac s, as well as socio-economic and human heal h p oblems (Hulme, 2007; Niineme s and Pe˜ nuelas, 2008; Pa ke e al., 1999). Al hough he numbe o na u alized species has inc eased exponen ially du ing he las decades (Seebens e al., 2017), we s ill ha e a poo unde s anding o he d i e s in luencing he in oduc ion o non-na i e plan species in o he u ban lo a compa ed o he d i e s in luencing he la e s ages o he in asion p ocess. Along he in asion p ocess om anspo o sp ead and in asion (Blackbu n e al., 2011; Colau i and MacIsaac, 2004), i has been well documen ed ha species ai s, clima ic condi- ions and socioeconomic ac o s ul ima ely in luence in asion success. Ne e heless, hese ac o s a e also likely o in luence he p obabili y ha a species is in oduced somewhe e in he i s place, and i is wo h no ing ha he species ai s de e mining in asion success migh no necessa ily be he same as hose de e mining hei delibe a e in oduc- ion, since he la e depends di ec ly on human pe cep ion, p e e ences and uses. Wi h his knowledge a hand, wha emains o be explo ed is how hese h ee main componen s (i.e. species ai s, clima e and socioeco- nomic con ex ) explain a ia ion in he p opo ion o non-na i e o na- men al species (non-na i e species numbe / o al species numbe ) in u ban pa ks. Indeed, he ela i e impo ance o each ac o is likely o a y ac oss a la ge e i o y i he e is a ia ion in clima ic and socio- economic a iables. Fo ins ance, se e e clima ic condi ions migh limi he impo ance o socioeconomic a iables in de e mining he p opo - ion o non-na i e o namen al species due o di ec en i onmen al il e ing p ocesses (K a e al., 2015). Howe e , wi h a elaxa ion o s ess ul condi ions due o mild clima ic condi ions o indi ec e ec s media ed by human ga dening ac i i ies, human popula ion size o hei income is expec ed o in luence he p opo ion o non-na i e o namen al species plan ed in u ban pa ks. C i ically, hese ex insic ac o s a e going o be media ed by plan ai s (Vaz e al., 2018). The e o e, knowledge o he ai p o iles o o namen al plan communi ies in conce wi h clima ic and socioeconomic co ela es will inc ease ou unde s anding o he p ocesses d i ing he in oduc ion and composi- ion o non-na i e lo as in u ban pa ks, and he es ablishmen o hese non-na i e species. In hese lines, p e ious wo k has shown ha socio- economic ac o s explain as much o he a ia ion o he dis ibu ion o non-na i e species es ablished in na u al ecosys ems as clima ic ac o s (Essl e al., 2011; Pyˇ sek e al., 2010). Howe e , we do no know o wha ex en he p opo ion o woody species na u alized in na u al ecosys- ems is associa ed wi h median species ai alues o he pa ks, and hei clima ic and socioeconomic a iables. In his s udy, we analyze he species plan ed in u ban pa ks ha a y in size and ounding yea . We speci ically ask (1) how clima ic and so- cioeconomic cha ac e is ics o he own in which he pa ks a e loca ed, de e mine he pa ks’ plan - ai p o iles and (2) how plan o igin (na i e s. non-na i e) and he in asion s a us (es ablished s. no es ablished in na u al ecosys ems) o he species plan ed in pa ks a e associa ed wi h plan ai s, clima ic and socioeconomic a iables? To answe hese ques ions, we ocused ou s udy on he peninsula e i o y o Spain (he ea e Spain) o se e al easons. Fi s , he o namen al use o non- na i e plan species in Spain is one o he main pa hways o in oduc- ion o po en ial in asi e species (Sanz Elo za e al., 2004). Wi h his de ailed in o ma ion, we can assess he ai p o iles o he communi ies o non-na i e u ban lo as ha a e mo e likely o escape om pa ks and become in asi e in na u al landscapes. Recen ly, 83 in asi e o po en- ially in asi e species we e iden i ied in nu se y ca alogues, a ailable o comme ce, including eigh egula ed in asi e species (Bay´ on and Vil` a, 2019). The exis ence o hese in asi e and po en ial in asi e spe- cies o consume s make i easie o be plan ed in pa ks and ga dens despi e ha i is o bidden. Second, Spain has a b oad ange o clima ic condi ions ( om Medi e anean and semia id o empe a e and con i- nen al clima es). We expec ha inland cold condi ions will impose a s ong il e o non-na i e woody species, while d ough e ec s in some coas al a eas in sou he n Spain will be amelio a ed by i iga ion du ing summe . Mo eo e , he d ough pe iods cha ac e is ic o mos clima es in Spain has e olu iona y limi ed he ai p o ile o na i e lo a o de elop species wi h a summe lowe ing pe iod and dense oliage (Godoy e al., 2009), and we would expec his o be e lec ed in non-na i e species. Consequen ly, we expec a b oade a ia ion o ai p o iles o non-na i e plan s in coas al owns. Finally, he owns selec ed a e no equally weal hy ac oss he coun y. In gene al, he weal h o a own and i s unemploymen a es migh ac as impo an d i e s di e en ia ing he non-na i e lo as o u ban pa ks (Schwa z e al., 2006; T en ano i e al., 2013; Vaz e al., 2017). 2. Me hods 2.1. U ban pa ks da ase We ob ained lo is ic ca alogs o 46 u ban pa ks and ga dens dis ibu ed in 23 owns ac oss he Spanish peninsula e i o y (Ap- pendix 1) om he ‘Vi i lospa ques’ da abase (www. i i lospa ques. es/; las accessed 12 Feb 2021), an online ool by he ‘Spanish Associ- a ion o Public Pa ks and Ga dens’ (AEPJP, 2010). This da abase p o- ides he mos upda ed and comple e in o ma ion o he species plan ed wi hin u ban pa ks in Spain as well as addi ionally impo an de ails such as o al pa k a ea, he ounding yea and he spa ial coo dina es o mos pa ks. Missing in o ma ion o pa k a ea was comple ed by using Google Maps ools and, o he yea he pa k was ounded, by ci y hall websi es. F om hese ca alogs, we selec ed he comple e lis o 486 woody plan species (i.e. ees, sh ubs, a bo eal cac i and palm ees). He bs we e excluded because hei plan ings can a y adically om yea o yea . Once he species lis was ob ained, we used The Plan Lis (2013) o ha monize scien i ic species names (www. heplan lis .o g; las accessed 5 Oc obe 2018). Non-speci ic axa, such as gene a wi h unspeci ied species epi he s, such as Rosa spp. o hyb ids such as Ci us ×au - an i olia, we e excluded. In he case o in aspeci ic axa (e.g. subspecies, a ie ies), such as Ced us a lan ica a . glauca, we only kep he binomial species names. Then, each species was classi ied, acco ding o hei o igin, as na i e o non-na i e in Spain, based on Sanz-Elo za e al. (2004) and Cas o iejo (2012). Fo non-na i e species, we consul ed hei es ablishmen s a us in Spain in (Sanz Elo za e al., 2004), which ollows he Richa dson e al. (2000) s a us de ini ions: es ablished and no es ablished in na u al ecosys ems. We included as es ablished spe- cies, hose ha can be ound g owing in na u al ecosys ems in Spain. These include na u alized species ha ha e es ablished pe sis en pop- ula ions, bu we he e also included non-na i es classi ied as casuals (i.e. species ha a e equen ly ound in na u al a eas bu do no a ain pe sis ing popula ions). We included casual non-na i es among he es ablished ones because he na u alized s casual classi ica ion is no e y p ecise o in oduced species in Spain, and because many species ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 3 conside ed casual a e known o cause en i onmen al impac s in na u al a eas (And eu e al., 2009). 2.2. Socioeconomic and clima ic da ase Clima ic a iables collec ed om Wo ldClim 2 (Fick and Hijmans, 2017) we e calcula ed o each pa k wi h QGIS so wa e (QGIS De el- opmen Team, 2009). Ras e maps wi h 1 km esolu ion we e ob ained o all he a iables a ailable in he sou ce: 11 empe a u e a iables and 8 p ecipi a ion a iables, as well as al i ude (Table 1a). Finally, we ob ained in o ma ion o nume ous socioeconomic a iables o he o al a ea o he 23 owns selec ed. Speci ically, we ob ained all he a iables a ailable a he Spanish S a is ics O ice (INE, 2017), which p o ide in o ma ion o mean alues be ween 2010 and 2016 (Table 1b) o 11 a iables associa ed wi h popula ion demog aphy, 4 wi h u baniza ion, and 6 wi h employmen and economy. We decided o ob ain all he in- o ma ion a ailable because we do no ha e ‘a p io i’ expec a ion o which a iables a e ele an o ou s udy. Such high dimensionali y was la e educed when pe o ming s a is ical analyses (see below). Due o he limi ed esolu ion o he da abase o socioeconomic Table 1 Clima ic and socioeconomic a iables used o desc ibe 46 u ban pa ks in 23 owns ac oss Spain. A) Clima ic a iables Type o a iable Va iable Code Kind o a iable Uni Fi s PCA selec ion Tempe a u e Annual mean empe a u e mean_ quan i a i e Celsius deg ee (◦C) * Mean diu nal ange diu n_ ang quan i a i e Celsius Iso he mali y iso he m quan i a i e % Tempe a u e seasonali y _season quan i a i e % Maximum empe a u e o he wa mes mon h max_ _wm quan i a i e Celsius Minimum empe a u e o he coldes mon h min_ _cm quan i a i e Celsius * Annual ange o empe a u e _ann_ g quan i a i e Celsius * Mean empe a u e o he we es qua e m _we _Q quan i a i e Celsius Mean empe a u e o he d ies qua e m _d ie_Q quan i a i e Celsius Mean empe a u e o he wa mes qua e m _wa m_Q quan i a i e Celsius Mean empe a u e o he coldes qua e m _cold_q quan i a i e Celsius P ecipi a ion Annual p ecipi a ion ann_p ecip quan i a i e mm P ecipi a ion o he we es mon h p ec_we M quan i a i e mm P ecipi a ion o he d ies mon h p ec_d ieM quan i a i e mm P ecipi a ion seasonali y p ec_seaso quan i a i e % P ecipi a ion o he we es qua e p ec_we Q quan i a i e mm P ecipi a ion o he d ies qua e p ec_d ieQ quan i a i e mm * P ecipi a ion o he wa mes qua e p ec_wa mQ quan i a i e mm P ecipi a ion o he coldes qua e p ec_coldQ quan i a i e mm Al i ude al s quan i a i e m a.s.l. B) Socioeconomic a iables Type o a iable Va iable Code Kind o a iable Uni Fi s PCA selec ion Basic demog aphy Numbe o esiden s n_ esid_10000 quan i a i e x 10 000 P opo ion o esiden s ≤14 yea s old n_0.14y quan i a i e % P opo ion o esiden s 15−64 yea s old n_15.64y quan i a i e % P opo ion o esiden s ≥65 yea s old n_.64y quan i a i e % Median age median_age quan i a i e yea s * P opo ion o na ional esiden s na ionals_pe cen quan i a i e % P opo ion o o eign esiden s o eign_pe cen quan i a i e % P opo ion o esiden s na i e om he own na i e_pe cen quan i a i e % * P opo ion o esiden s bo n ou side he own bo n_ou s_pe cen quan i a i e % Na ali y a e na ali y_pe _ housand quan i a i e ‰ Mo ali y a e mo ali y_pe _ housand quan i a i e ‰ U banis ics Numbe o homes n_homes_10000 quan i a i e x 10 000 Numbe o con en ional homes (Ca as al) con _homes_10000 quan i a i e x 10 000 Mean household size (numbe o inhabi an s pe home) home_size quan i a i e * P opo ion o single-pe son homes single_pe s_home_pe cen quan i a i e % Employmen and economics Unemploymen a e unemploy_pe cen quan i a i e % Wo king popula ion in ac i e age (20−64 yea s old) X20.64y_pe cen _ocupa ed_in_ac i e quan i a i e % * Ac i e popula ion ac i i y_pe cen quan i a i e % Indus y wo ke s indus y_wo ke s_pe cen quan i a i e % Se ice wo ke s se ice_wo ke s_pe cen quan i a i e % A e age money incoming pe home a g_inc_eu o_10000 quan i a i e x 10 000 € * A ea o he own a ea_c quan i a i e km 2 C) Pa k-dependen a iables Type o a iable Va iable Code Kind o a iable Uni Pa k-dependen A ea o he pa k a ea_m_sq quan i a i e m 2 Founding yea o he pa k yea quan i a i e Table 1. A i s compila ion o clima ic a iables (A) was pe o med h ough a sys ema ic sea ch om Wo ldClim 2 (Fick and Hijmans, 2017). The i s compila ion o socioeconomic a iables (B) was pe o med h ough a sys ema ic sea ch om he Spanish S a is ics O ice (INE, 2017). Pa k-dependen a iables (C) we e mainly ob ained om AEPJP (2010), and seconda y, om Google Map ools (a ea) and ci y hall websi es (yea ). Finally, we made a selec ion using a Pea son co ela ion analysis (Appendix 2, Fig. A2.1 and A2.2) and PCA (Fig. 1a and b) in which we applied a b oken-s ick c i e ion (Appendix 2, Fig. A2.4 and A2.5), as desc ibed in he Me hods. * Va iables ma ked wi h an as e isk we e inally selec ed by he PCA and b oken-s ick me hod. ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 4 a iables, possible a ia ions below he own le el, such as dis ic s o neighbo hoods, we e no possible o add ess. The e o e, he socioeco- nomic da a o pa ks wi hin he same ci y we e he same. We ob ained da a om a wide ange o own sizes — om e y densely popula ed (e.g. Ba celona) o e y small owns (e.g. Ciudad Real)— and clima ic con- di ions — om a we empe a e clima e (e.g. Bilbao) o a ho and d y Medi e anean clima e (Lo ca)—. The a e age numbe o pa ks wi hin he same ci y is 2, and only 2 owns ha e mo e han 3 pa ks (Appendix 1). 2.3. Plan ai s da ase We used se e al sou ces o in o ma ion o ob ain o gan-le el and whole-plan ai s a he species le el. The majo i y o plan ai s we e ex ac ed om he TRY Da abase (Ka ge e al., 2011). We pe o med a second sea ch in se e al in e ne da abases (Table 2). Fo each species, we ob ained 21 plan ai s (17 con inuous and 4 bina y) ela ed o whole-plan cha ac e is ics, lea es, ep oduc i e o gans ( lowe s and dispe sal uni s), plan lowe ing and ui ing phenology, and ole ances o se e al en i onmen al s esso s such as os (minimum absolu e empe a u e ole a ed and numbe o os days pe yea ), shade, d ough , wa e logging and i e, as well as he minimum and maximum ha diness alues and i s ange (Table 2). Ha diness zones a e ca o- g aphical s anda diza ions o he a e age annual minimum win e empe a u es di ided in o 10-deg ee F zones (S´ anchez de Lo - enzo-C´ ace es, 2004; USDA, 2012). Thus, he ha diness alues o a gi en species is de ined as he abili y o su i e and g ow in a speci ic ange o ha diness zones. We conside he lowe ha diness zone alue ha he species can ole a e as “minimum ha diness”, he highes alue as “maximum ha diness”, and he di e en be ween bo h alues, he “ ange o ha diness”. Spain includes ha diness zones 7a (-17.8 ◦C o -15 ◦C) o 11b (7.2 ◦C–10 ◦C; Fick and Hijmans, 2017; S´ anchez de Lo - enzo-C´ ace es, 2004). This comp ehensi e sea ch did un o una ely no ende ai in o - ma ion o all species. The e o e, we excluded o u he analyses i e ai s wi h da a missing o mo e han 50 % o he species (Table 2). Fo he emaining ai s, missing da a was impu ed. P e ious wo k has shown ha impu ing missing alues is be e han simply emo ing missing-da a a iables o missing-da a species, as emo ing da a could bias he esul s (Penone e al., 2014). We applied nonpa ame ic missing alue impu a ion using andom o es s implemen ed in he R package ‘missFo es ’ (S ekho en and Buhlmann, 2012), which uses a andom o es ained on he obse ed alues o p edic he missing alues. This impu a ion me hod can handle mul i a ia e da a consis ing o con in- uous and ca ego ical a iables simul aneously, as was he case in ou s udy. O e all, a e se en i e a ions, he ou -o -bag no malized oo mean squa ed e o was low (1.1608; PFC 0.0295), indica ing a good impu a ion pe o mance (S ekho en and Buhlmann, 2012). 2.4. S a is ical analyses 2.4.1. O e iew Due o he high numbe o a iables ob ained, and some o hem showing high collinea i y, we decided o educe he numbe o a iables using s a is ical ools wi h he inal objec i e o a oid o e i ing he s a is ical models (King and Jackson, 1999; Zhou e al., 2010). We i s buil a da abase o he plan - ai p o ile o he pa ks, calcula ing he median alue o each quan i a i e ai and he mean alue o each bi- na y ai ( equency) o each pa k. We conside ed each pa k as a eplica e. The educ ion o a iables was done on each o he h ee main g oups o a iables selec ed (i.e. clima ic a iables, socioeconomic a iables, and pa k ai p o ile) ollowing h ee complemen a y s eps. Fi s , we pe o med a co ela ion ma ix o iden i y he mos co ela ed a iables (Appendix 2). I wo a iables we e closely co ela ed ( -Pea son >0.70), we emo ed one o hem. Second, we pe o med a p incipal componen analysis (PCA), in which we used a b oken s ick c i e ion (Simon e al., 2011) on he i s and second dimensions (Ap- pendix 2) o iden i y he main a iables explaining he ob ained PCA. Thi d, we pe o med Lasso eg ession models (F iedman e al., 2010; Simon e al., 2011; Tibshi ani, 1996) o exclude non-in o ma i e explana o y a iables (Hesamian and Akba i, 2019). Wi h he comple- ion o hese h ee s eps, we ob ained he inal se o a iables, which we e used o bes p edic a ia ion in he p opo ion o plan o igin (na i e s. non-na i e) and in he in asion s a us (es ablished s. no es ablished in na u al ecosys ems). This s a is ical p ocess is ully explained in Appendix 3. Acco ding o his p ocedu e, he i s and second axes o he PCA on clima ic a iables explained 39 % and 35 % o he a ia ion, espec i ely (Fig. 1a). We selec ed i e clima ic a iables (annual mean empe a u e, p ecipi a ion in d ies qua e , minimum empe a u e in coldes mon h, and annual ange o empe a u es; Table 1a). Fo he PCA on socio- economic a iables, he i s and second p incipal axes explained 37 % and 25 % o he a ia ion, espec i ely (Fig. 1b). We selec ed i e so- cioeconomic a iables (mean household size, median age o inhabi an s, pe cen o na i e popula ion, pe cen o wo king popula ion be ween 20 and 64 yea s old in ac i e, and a e age incoming money pe home; Table 1b). Finally, he i s and second p incipal axes o he PCA in ol ing pa k ai p o iles explained 28 % and 19 % o he a ia ion, espec i ely (Fig. 1c). We selec ed i e plan ai s (minimum, maximum and ange o ha diness, ole ance o shade, and ha ing conspicuous lowe s; Table 2). Wi h he inal se o a iables selec ed, we hen pe o med gene al- ized linea models (GLMs), using he ‘glm’ unc ion om he R package ‘s a s’ (R Co e Team, 2019) wi h a linea combina ion o p e iously selec ed a iables as p edic o s in each case, he species ichness o he pa ks as p io weigh s, and a ea and ounding yea o he pa k as co a ia es because bigge and olde pa ks ha e had mo e space and ime o accumula e a wide di e si y o species. 2.4.2. Rela ionships be ween plan - ai p o ile and clima ic and socioeconomic cha ac e is ics To answe he i s ques ion, namely whe he clima ic and socio- economic a iables explain a ia ion in he unc ional plan - ai p o ile ac oss pa ks, we conside ed in he Lasso eg essions all he clima ic and socioeconomic a iables p eselec ed as independen a iables, while we ea ed each p eselec ed ai (i.e. minimum, maximum and ange o ha diness, ole ance o shade and ha ing conspicuous lowe s) as dependen a iable in each model (see ‘O e iew’). A e he educ ion o a iables, we pe o med i e GLMs (Poisson dis ibu ion wi h he quasipoisson se ing o accoun o o e - dispe sion), one o each ai selec ed o he pa k p o ile. P edic o s we e a linea combina ion o clima ic and socioeconomic ac o s p e- iously selec ed in he Lasso eg ession (i.e. minimum empe a u e in he coldes mon h, annual empe a u e ange, and household size; Table A4.1 om Appendix 4), and a ea and ounding yea o he pa k we e included as co a ia es. 2.4.3. In luence o plan - ai p o ile, clima ic and socioeconomic cha ac e is ics on he p opo ion o non-na i e species To answe he second ques ion, namely, whe he species o igin: na i e s. non-na i e; and es ablishmen s a us: es ablished s. no es ablished; can be explained by clima ic and socioeconomic a iables, and he pa ks’ plan - ai p o ile, we i s ob ained he numbe o na i e and non-na i e species wi hin each pa k, and o he non-na i e ones, he numbe o species ha ha e es ablished in na u al ecosys ems (being in asi e, na u alized o casual, acco ding o Sanz Elo za (S´ anchez de Lo enzo-C´ ace es, 2004; USDA, 2012)(2004) and o he wo ks (Bay´ on and Vil` a, 2019; Gass´ o e al., 2010). We used a pai ed S uden ’s - es (‘ . es ’ unc ion o he ‘s a s’ basic R package; R Co e Team, 2019) o es whe he he numbe s o non-na i e and na i e species we e simila . Simila ly, we es ed whe he he numbe s o no es ablished and es ablished non-na i e species we e simila . ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 5 Table 2 T ai s used o desc ibe woody plan species in 46 u ban pa ks in 23 owns ac oss Spain. (B¨ a els and Schmid (2014); Bo ´ anica (2014); B ines e al. (1997); Cen aal Bu eau oo de S a is iek (2003); CSIC (2014); Cze epano (1995); Gallaghe and Leishman (2012); Hin ze e al. (2013); Moles e al. (2004); Mo ales (2002); Plan s Fo A Fu u e (2010); S´ anchez de Lo enzo-C´ ace es (1999); Uni e sidad de M´ alaga (2011); USDA (2008); Whea ley (2009) and Wyse-Jackson (2006)). Type o ai T ai Code Kind o a iable Uni % eal da a % impu a ed da a Fi s PCA selec ion Da a sou ces beyond TRY Whole plan Max heigh heigh _m quan i a i e m 100 % 0 % 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 16 Max li espan — quan i a i e yea s 44 % Va .Ex. 1, 2, 3, 4, 5, 6, 7, 11 Lea es A ea lea _a ea_sq_mm quan i a i e sq. mm 54 % 46 % 1, 2, 3, 4, 5, 6, 7, 10, 17 Lamina leng h lea _leng h_cm quan i a i e cm 85 % 15 % 1, 2, 3, 4, 5, 6, 7, 10, 17 Lamina wid h lea _wid h_cm quan i a i e cm 63 % 37 % 1, 2, 3, 4, 5, 6, 7, 10, 17 Lea ype lea _ ype_0 o1 bina y 0 =b oadlea ed 97 % 3 % 1, 2, 3, 4, 5, 6, 7, 10, 18 1 =coni e Rep oduc i e o gans Flo al uni size — quan i a i e mm 9 % Va .Ex. 1, 2, 3, 4, 5, 6, 7, 10 Conspicuous lowe isual_ lowe _0 o1 bina y 0 =No 93 % 7 % * 1, 2, 3, 4, 5, 6, 7, 10 1 =Yes Pollina ion synd ome pollin_synd_0 o1 bina y 0 = Anemophilous 93 % 7 % 1, 2, 3, 4, 5, 6, 7, 10, 12 1 = En omophilous Gymnospe m lowe s gymnosp_ lowe _0 o1 bina y 0 =No 93 % 7 % 1, 2, 3, 4, 5, 6, 7, 12 1 =Yes Dispe sal uni mass — quan i a i e g 15 % Va .Ex. 1, 2, 3, 4, 5, 6, 7, 10, 12, 17 Plan Phenology Rep oduc i e phenology iming phenol_ iming quan i a i e o dinal mon h 85 % 15 % 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 16 Lea phenology lea _phen_0 o1 bina y 0 =deciduous 97 % 3 % 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 15, 18 1 =e e g een Tole ances To os empe a u e ol_ os _ emp quan i a i e Celsius 82 % 18 % 1, 2, 3, 4, 5, 6, 7, 9 To os days — quan i a i e num. days 32 % Va .Ex. 1, 2, 3, 4, 5, 6, 7 To shade ol_shade_0 o5 quan i a i e 1−5 92 % 8 % * 1, 2, 3, 4, 5, 6, 7, 9, 11 To d ough ol_d ough _0 o5 quan i a i e 1−5 89 % 11 % 1, 2, 3, 4, 5, 6, 7, 9, 11 To wa e logging ol_wa e logging_0 o5 quan i a i e 1−5 76 % 24 % 1, 2, 3, 4, 5, 6, 7, 9 To i e — quan i a i e 1−5 29 % Va .Ex. 1, 2, 3, 4, 5, 6, 7, 11 Ha diness min. ha diness_min quan i a i e 1−12 67 % 33 % * 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 Ha diness max. ha diness_max quan i a i e 1−12 67 % 33 % * 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 Ha diness ange ha diness_ ange quan i a i e 1−12 Calcula ed di ec ly: di e ence be ween max. and min. alues * Calcula ed Da a sou ces Num. Sou ce e e ence 1 B ines R, Tejuelo I, Bel ´ an P and Balague ´ A. (1997) Guía Ve de. h ps://www.guia e de.com/. Accessed 1 Sep 2017 2 CSIC A bolapp. (2014) In: A bolapp. h p://www.a bolapp.es/. Accessed 1 Sep 2017 3 Mo ales J. (2002) In oja dín. h p://www.in oja din.com/. Accessed 1 Sep 2017 4 S´ anchez de Lo enzo-C´ ace es JM. (1999) ´ A boles O namen ales. h p://a boleso namen ales.es/. Accessed 1 Sep 2017 5 Uni e sidad de M´ alaga. (2011) Ja dín Bo ´ anico de la Uni e sidad de M´ alaga. h p://www.ja dinbo anico.uma.es/ja dinbo anico/index.php. Accessed 1 Sep 2017 6 Wyse-Jackson P. (2006) Missou i Bo anical Ga den. h ps://www.missou ibo anicalga den.o g/. Accessed 1 Sep 2017 7 Bo ´ anica Y Ja dines. (2014) In: Bo ´ anica Y Ja dines. h p://www.bo anicayja dines.com/. Accessed 1 Sep 2017 8 B¨ a els A. and Schmid P. A. (2014) Enzyklop¨ adie de Ga engeh¨ olze, 2nd edn. Ulme E. Ve lag 9 Plan s Fo A Fu u e (PFAF). (2010) In: Plan s Fo A Fu u e. h ps://p a .o g/use /De aul .aspx. Accessed 1 Jun 2017 10 Wea hley, R. (2009) B and T Wo ld Seeds. h p://b-and- -wo ld-seeds.com/. Accessed 1 Jun 2017 11 USDA. (2008) USDA Plan s Da abase. h ps://plan s.usda.go /ja a/. Accessed 1 Jun 2017 12 Hin ze C, Heydel F, Hoppe C, e al (2013) D3: The Dispe sal and Diaspo e Da abase – Baseline da a and s a is ics on seed dispe sal. Pe spec i es in Plan Ecology, E olu ion and Sys ema ics 15:180–192. 13 Cen aal Bu eau oo de S a is iek BioBase (2003) In: Cen aal Bu eau oo de S a is iek. h ps://www.cbs.nl/nl-nl/onze-diens en/me hoden/classi ica ies/o e ig/bio base-2003/biobase-2003. Accessed 1 Jun 2017 14 Cze epano SK (1995)Vascula plan s o Russia and adjacen s a es ( he o me USSR). Camb idge Uni e si y P ess, New Yo k 15 Zanne AE, Tank DC, Co nwell WK, e al (2004) Th ee keys o he adia ion o angiospe ms in o eezing en i onmen s. Na u e 506:89–92. 16 Moles AT, Fals e DS, Leishman MR, Wes oby M (2012) Small-seeded species p oduce mo e seeds pe squa e me e o canopy pe yea , bu no pe indi idual pe li e ime. Jou nal o Ecology 92:384–396. 17 Gallaghe RV, Leishman MR (2012) A global analysis o ai a ia ion and e olu ion in climbing plan s. Jou nal o Biogeog aphy 39:1757–1771. 18 Panchen ZA, P imack RB, No d B, e al (Panchen e al., 2014) Lea ou imes o empe a e woody plan s a e ela ed o phylogeny, deciduousness, g ow h habi and wood ana omy. New Phy ol 203:1208–1219. Table 2. A i s compila ion o plan ai s was pe o med h ough a sys ema ic sea ch in he TRY Da abase (Ka ge e al., 2011). A second sea ch was pe o med o comple e he da abase —see Da a Sou ces. Then, hose a iables o which we had mo e han 50 % o he da a we e selec ed, and, on hem, we made a nonpa ame ic missing alue impu a ion by andom o es (S ekho en and Buhlmann, 2012). ‘Va .Ex.’ indica es a iables excluded om impu a ion because no enough da a. Finally, we made a selec ion using a Pea son co ela ion analysis (Appendix 2, Fig. A2.3) and PCA (Fig. 1c) in which we applied a b oken-s ick c i e ion (Appendix 2, Fig. A2.6) as desc ibed in he Me hods. * Va iables ma ked wi h an as e isk we e inally selec ed by he PCA and b oken-s ick me hod. ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 6 Fig. 1. PCAs o ela ions o a iables among pa ks. P incipal componen analyses (PCA) o A) clima ic a iables o each pa k, B) socioeconomic a iables o he locali ies o each pa k and C) median alues o he plan ai s in each pa k. See Appendix 1 o he lis o locali ies and codes o pa ks, and Ta- bles 1 and 2 o he desc ip ion o ai s and a iables. (Fo in e p e a ion o he e e ences o colou in his igu e legend, he eade is e e ed o he web e sion o his a icle). ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 7 Then, o each pa k we calcula ed he ollowing p opo ions o spe- cies: •P opo ion o non-na i e species, pAi=Ai Ni+Ai •P opo ion o es ablished non-na i e species, pEi=Ei NEi+Ei Whe e Ni is he numbe o na i e species in pa k i; Ai is he numbe o non-na i e species in pa k i; NEi is he numbe o non-na i e species ha ha e no es ablished in na u al ecosys ems o pa k i; and Ei is he numbe o non-na i e species ha ha e es ablished in na u al ecosys- ems o pa k i. We es ed whe he hese p opo ions a ied signi ican ly ac oss pa ks using a Pea son’s Chi-squa ed es (‘chisq. es ’ unc ion o he R package ‘s a s’; R Co e Team, 2019). A e he educ ion o he numbe o a iables by using co ela ions, PCA and b oken s ick c i e ia, we conside ed o he lasso eg essions all he emaining a iables and ai s p eselec ed as independen a iables, while we ea ed he p opo ion o non-na i e species and he p opo ion o es ablished species as dependen a iables in each model (see ‘O e iew’). Then we pe o med wo GLMs (binomial dis ibu ion), one o each p opo ion. P edic o s we e a linea combina ion o ai s, cli- ma ic and socioeconomic ac o s p e iously selec ed in he Lasso eg ession (i.e. annual empe a u e ange, household size, median age o own inhabi an s, pe cen o wo king popula ion in ac i e age (20−64 yea s old wi h job), maximum ha diness and ange o ha diness; Table A4.2 om Appendix 4), and a ea and ounding yea o he pa k we e included as co a ia es. 2.5. Da a esou ces The da a unde pinning he analyses, epo ed in his pape , a e deposi ed in he Zenodo eposi o y a h ps://doi.o g/10.5281/zen- odo.4095422 (Bay´ on e al., 2020) 3. Resul s O e all, he da abase has 486 woody species. On a e age, he e we e 53 ±5.14 (mean ±se) species pe pa k and he maximum numbe was 144 species. Many species appea only in one o a ew pa ks. Each species is in 5 ±0.26 (mean ±SE) pa ks. Mo e p ecisely, 180 species (37.04 %) appea in only one pa k each, 68 species (13.99 %) appea in wo pa ks, and 45 species (9.26 %) in h ee pa ks, whe eas only 11 species (2.25 %) occu in hal o he pa ks o mo e (Appendix 1). The lis o mos common species and i s s a us we e: Cup essus sempe i ens (32 pa ks; es ablished), Cel is aus alis (26 pa ks; na i e), Robinia pseudoa- cacia (26 pa ks; es ablished), S yphnolobium japonicum (25 pa ks, non- na i e), Ced us a lan ica (24 pa ks; es ablished), Ced us deoda a (24 pa ks; es ablished), Magnolia g andi lo a (24 pa ks; non-na i e), Ce cis siliquas um (23 pa ks; es ablished), Lau us nobilis (23 pa ks; na i e), Phoenix cana iensis (23 pa ks; non-na i e) and Populus alba (23 pa ks; na i e). Acco ding o he o igin, we ound 86 na i e species (17.70 %) and 400 non-na i e species (82.30 %), 130 (26.75 %) o which ha e es ablished in na u al ecosys ems (Table 3). 3.1. Pa k cha ac e iza ion The co elog am o clima ic a iables (Fig. A2.1 om Appendix 2) shows ha he e is a s ong co ela ion be ween di e en ypes o cli- ma ic a iables. Values o p ecipi a ion, excep seasonali y, showed e y high co ela ions be ween each o he (minimum Pea son’s =0.49 be ween p ecipi a ion o he d ies qua e and he coldes qua e ). The i s axis o he clima ic PCA accoun ed o 38.5 % o he o e all clima ic a ia ion ac oss pa ks, and i was mainly explained by he opposi e end be ween p ecipi a ion and mean empe a u e in he d ies qua e . The second PCA axis accoun ed o 34.9 % o he obse ed clima ic a ia ion ac oss pa ks, and i was explained by he same beha io o he minimum empe a u e in he coldes mon h and he mean in he we es qua e (Fig. 1a). Among socioeconomic a iables, he highes co ela ions (Fig. A2.2 om Appendix 2) was obse ed be ween he numbe o esiden s and numbe o homes (Pea son’s =1). A e age household sizes in he owns o he pa ks we e di ec ly ela ed o he p opo ion o kids and adul inhabi an s (Pea son’s =0.62 o kids unde 14 yea s old, and = 0.60 o adul s be ween 15 and 64 yea s old), and in e sely o he p opo ion o people o e 64 yea s old ( =-0.70). This p opo ion o people o e 64 is in addi ion di ec ly ela ed wi h he median age o he popula ion (Pea son’s =0.97). Mo eo e , we ound ha o he so- cioeconomic PCA, household size and median age we e bo h dis ibu ed along he i s axis (36.7 %) bu in opposi e di ec ions. Median age o he popula ion ollowed a e y simila pa e n o he pe cen age o wo ke s in he se ice sec o wi hin he i s socioeconomic PCA axis. Finally, he pe cen age o employed people, as well as he a e age income pe home, we e bo h dis ibu ed along he second PCA axis (25 %) and in he same di ec ion (Fig. 1b). Rega ding he pa ks’ plan - ai p o iles (Table 2), some a iables we e highly co ela ed (Appendix 2, ig. A2.3). Fo example, en o- mophilous pollina ion was co ela ed wi h se e al o he ai s such as he p esence o conspicuous lowe s (Pea son’s =1), maximum heigh (Pea son’s =-0.82) and he ole a ed minimum empe a u e (Pea - son’s =0.52). As expec ed, he e was also a high co ela ion be ween cold ole ance and he minimum alue o ha diness (Pea son’s =0.79). O he co ela ions wo h men ioning we e hose ound be ween he ype o lea (coni e needle – b oad lea ) and whe he o no species a e gymnospe m (Pea son’s =0.98). Lea size a iables we e all closely co ela ed wi h each o he (Pea son’s =0.76 o wid h s a ea; 0.76 o a ea s leng h; 0.73 o wid h s leng h). Wi h all his a ia ion, he i s axis o he plan ai PCA accoun ed o 28 % o he o e all ai a i- a ion and i was mainly explained by an opposi e end be ween mini- mum ha diness, ha diness ange and he p esence o conspicuous lowe s. In addi ion, maximum ha diness and lea wid h was also dis ibu ed along he i s axis o a ia ion bu o e all had a less s a is- ical weigh . Shade and d ough ole ance we e pa ly ela ed o he second axis o he PCA in opposi e di ec ions (Fig. 1c). 3.2. Rela ionships be ween plan - ai p o iles and clima ic and socioeconomic cha ac e is ics A e educing model dimensionali y, wo clima ic a iables we e e ained o explain some a ia ion in he ai p o ile ac oss pa ks. These a iables we e he minimum empe a u e in he coldes mon h, and he ange o empe a u es. The emaining p edic o s, hese a e, household size, ounding yea o he pa k and pa k a ea, did no explain any o he ai s selec ed as dependen a iables (Table 4). Speci ically, minimum and maximum plan ha diness as well as he p esence o conspicuous lowe s we e posi i ely ela ed o minimum empe a u e in he coldes mon h. On he o he hand, ha diness ange and shade ole ance we e nega i ely ela ed o minimum empe a u e in he coldes mon h (Fig. 2a). Simila ly, we obse ed a signi ican posi i e ela ionship be- ween he annual ange o empe a u es and he minimum and maximum ha diness (i.e. highe maximum ha diness alues means plan s a e less ole an o cold), while he ela ionship be ween he annual ange o empe a u es and he ole ance o shade was nega i e. Howe e , he e was no signi ican ela ionship be ween he annual Table 3 Numbe o woody o namen al plan species by s a us and g ow h o m in 46 u ban pa ks in 23 owns o Spain. T ees Sh ubs Palms A bo eal Cac i To al Na i e 59 26 1 0 86 Non-na i e no es ablished 154 85 30 1 270 Non-na i e es ablished 95 30 4 1 130 To al 308 141 35 2 486 ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 8 ange o empe a u es and he ha diness ange, no wi h he p esence o isual and conspicuous lowe s (Fig. 2b). In luence o plan - ai p o iles, clima ic and socioeconomic cha - ac e is ics on he p opo ion o non-na i e species O e all, he e is a g ea e p esence o non-na i e (39.2 ±4.15; mean ±se) han o na i e species (14.2 ±1.27; pai ed - es ; =7.475; p- alue <0.01; Fig. 3a) ac oss pa ks. Fo he case o non-na i e species, he numbe o species ha a e no known o ha e es ablished in na u al ecosys ems (21.15 ±2.06) is signi ican ly la ge han he numbe o es ablished species (18.02 ±2.27; pai ed - es ; =2.4393; p- alue = 0.0187; Fig. 3b). The p opo ion o non-na i e species and he p opo - ion o es ablished species a e bo h signi ican ly he e ogeneous ac oss pa ks (Chi-squa ed =132.98, and 148.17, espec i ely; p <0.01 in bo h cases). A e educing model dimensionali y, only one clima ic a iable (annual ange o empe a u e), wo socioeconomic a iables (mean o household size, and median age o inhabi an s) and one plan ai o he pa k p o ile ( ange o ha diness) explained he p opo ion o non-na i e species. The emaining p edic o s (pe cen age o ac i e popula ion, maximum ha diness, ounding yea o he pa k, and pa k a ea) did no explain any o he p opo ions selec ed as dependen a iables. The GLM analysis indica es (Table 5) a signi ican nega i e ela- ionship be ween annual ange o empe a u e and he p opo ion o es ablished species bu no wi h he p opo ion o non-na i e species (Fig. 4a). Rega ding socioeconomic a iables, mean o household size and median age bo h signi ican ly explained he p opo ion o non- na i e species bu no he p opo ion o es ablished species (Fig. 4b, c). Finally, a ia ion in ha diness ange o he pa k’s p o ile nega i ely explained he p opo ion o non-na i e species, bu i did no explain he p opo ion o es ablished species (Fig. 4d). 4. Discussion We ha e a poo unde s anding o he combina ion o plan ai s, clima e a iables and socioeconomic ac o s guiding he plan ing on non-na i e woody plan species in u ban pa ks. This knowledge is essen ial o iden i y how di e en d i e s in luence he success o non- na i e species om in oduc ion o in asion. He e, we p esen insigh s om a la ge ep esen a ion o u ban pa ks ac oss Spain showing ha hey ha bo a mo e non-na i e han na i e plan species. In e es ingly, his high p opo ion o non-na i e woody species (82.3 %) is no asso- cia ed wi h a pa icula se o axa. Ra he , Spanish pa ks p esen a high species u no e , meaning ha he as majo i y o woody plan species appea in one o e y ew pa ks, while e y ew species a e p esen in he majo i y o pa ks. The a e age pe cen age o non-na i e woody species in Spanish u ban pa ks is much highe han in Cen al Eu opean u ban lo as (Pyˇ sek, 1998), and many o he egions (Dangulla e al., 2019; de F ei as e al., 2019; Jha e al., 2019; Temple on e al., 2019), whe e he a e age ep esen a ion o non-na i e species is be ween 40 % and 50 %. In line wi h his inding, he pe cen age o non-na i e species a ailable in Spanish nu se ies is 76 % app oxima ely (Bay´ on and Vil` a, 2019). The small di e ence be ween he pe cen age in pa ks and nu se ies is p obably no signi ican , and can be due o he ac ha he s udy o Spanish nu se ies includes all ypes o plan g ow h o ms, while his s udy only ocus on woody species. Mo eo e , many plan s in pa ks a e no longe sold in Spanish nu se ies (Bay´ on and Vil` a, 2019) such as Buddleja madagasca iensis, Casua ina cunninghamiana, Elaeagnus pungens, F axinus pennsyl anica, Pa kinsonia aculea a, Pi ospo um undula um, Ricinus communis and Schinus molle. We ha e ound ha he plan ai composi ion o u ban pa ks can be explained by a combina ion o socioeconomic and clima ic a iables. We obse ed a ia ion in he p opo ion o species wi h conspicuous lowe s (which is a di ec p oxy o he pollina ion synd ome) ac oss u ban pa ks, and his a ia ion was explained by minimum empe a u e in he coldes mon h. Species wi h en omophilous pollina ion end o be poo ly ole an o os , p obably due o he dependence o hei pollina ing insec s on milde empe a u es. Meanwhile, wind-pollina ed plan s ha e a wide ange o ole ance o os . Fo ins ance, oak species a e known o be os ole an , whe eas o he species like palms do no show he same adap a ions. The la e a e p edominan ly ound in owns wi h oceanic clima e, whe e os is a a e phenomenon. The pollina ion Table 4 Gene al Linea ized Models on plan ai s. A) Minimum ha diness Es ima e S d. E o alue P (>| |) (In e cep ) 1.5667 0.3541 4.4244 0.0001 *** Minimum empe a u e o he coldes mon h 0.0456 0.0071 6.4694 < 0.0001 *** Annual ange o empe a u e 0.0191 0.0048 3.9906 0.0003 *** Mean household size −0.0271 0.0448 −0.6033 0.5497 Founding yea o he pa k −0.0002 0.0002 −1.1550 0.2549 . A ea o he pa k −1.9019E- 07 1.2108E- 07 −1.5708 0.1241 B) Maximum ha diness Es ima e S d. E o alue P (>| |) (In e cep ) 2.1459 0.1665 12.8890 < 0.0001 *** Minimum empe a u e o he coldes mon h 0.0180 0.0033 5.4110 < 0.0001 *** Annual ange o empe a u e 0.0082 0.0023 3.6049 < 0.0001 *** Mean household size −0.0216 0.0209 −1.0313 0.3086 Founding yea o he pa k −0.0001 0.0001 −0.9207 0.3628 A ea o he pa k −1.8047E- 08 5.3817E- 08 −0.3353 0.7391 C) Range o ha diness Es ima e S d. E o alue P (>| |) (In e cep ) 1.2575 0.4182 3.0068 0.0045 ** Minimum empe a u e o he coldes mon h −0.0288 0.0084 −3.4244 0.0014 ** Annual ange o empe a u e −0.0080 0.0057 −1.3926 0.1714 Mean household size −0.0304 0.0513 −0.5929 0.5566 Founding yea o he pa k 0.0001 0.0002 0.6964 0.4902 A ea o he pa k 6.0555E- 08 1.2795E- 07 0.4733 0.6386 D) Tole ance o shade Es ima e S d. E o alue P (>| |) (In e cep ) 2.0327 0.5283 3.8473 0.0004 *** Minimum empe a u e o he coldes mon h −0.0376 0.0107 −3.5268 0.0011 ** Annual ange o empe a u e −0.0320 0.0072 −4.4644 0.0001 *** Mean household size 0.0829 0.0687 1.2063 0.2348 Founding yea o he pa k −0.0003 0.0002 −1.3355 0.1893 A ea o he pa k −1.2227E- 07 1.6867E- 07 −0.7249 0.4727 E) P esence o conspicuous lowe s Es ima e S d. E o alue P (>| |) (In e cep ) −3.3205 1.1389 −2.9156 0.0058 ** Minimum empe a u e o he coldes mon h 0.0815 0.0220 3.7109 0.0006 *** Annual ange o empe a u e 0.0273 0.0146 1.8666 0.0693 . Mean household size 0.1330 0.1388 0.9586 0.3435 Founding yea o he pa k 0.0008 0.0005 1.5061 0.1399 A ea o he pa k −3.0225E- 07 3.8541E- 07 −0.7842 0.4375 Gene alized linea models o he i e plan ai s selec ed as dependen a iables, e sus clima ic and socioeconomic a iables p eselec ed by lasso eg ession (Table A4.1 om Appendix 4) as independen a iables. ** 0.001 <p ≤0.01. *** p ≤0.001, o he wise non signi ican . G aphical ep esen a ion in Fig. 2. ´ A. Bay´ on e al. U ban Fo es y & U ban G eening 63 (2021) 127215 9 synd ome can change in u ban lo as depending on hei na i e and non- na i e o igin. Fo ins ance, A onson e al. (2007) documen ed ha conspicuous lowe s, ha ends o be beau i ul, di e in hei pollina ion equi emen s; howe e , we did no ind his pa e n in ou s udy. Di - e ences be ween esul s migh be ela ed o he ac ha he s udy o A onson e al. (2007) was conduc ed in si es wi h simila en i onmen al condi ions, while ou s udy includes owns wi h a wide ange o clima es om con inen al o Medi e anean, and om inland o oceanic clima ic condi ions. Besides cold ac ing as a il e o ep oduc ion synd omes, we ound ha he ole ance o shade inc eased wi h highe minimum empe a u e in he coldes mon h and wi h wide he mal ange. In egions wi h an oceanic clima e, such as he no he n coas , win e s a e milde and cloudiness is mo e equen and las s longe , especially in he summe mon hs, han in he es o Spain. Howe e , in egions whe e he clima e is mo e con inen al, as in he pla eaus, win e s a e colde and summe s a e no only ho e bu also e y sunny wi h high e apo anspi a ion a es (AEMET, 2019). These di e ences a e likely o cing plan species selec ed o be plan ed in oceanic clima es o be mo e ole an o inso- la ion, educing lea a ea o a oid wa e loss, while plan s wi h la ge lea es end o be dis ibu ed in a eas wi h highe wa e a ailabili y and lowe i adiance (Holmg en e al., 2012; Ma kes eijn and Poo e , 2009). Finally, he minimum and maximum ha diness alues o he plan s we e di ec ly ela ed o bo h minimum empe a u e in he coldes mon h and highe annual anges o empe a u e. This is indeed an ob ious ela ionship, as ha diness is a p oxy o he ole ance o low empe a u es (S´ anchez de Lo enzo-C´ ace es, 2004; USDA, 2012), and i ep esen s a p ima y ac o in selec ing which species a e plan ed. Speci ically, hose species wi h high ole ance o cold, a e usually no plan ed in wa m places e en i hey could su i e he e. This explana- ion is suppo ed by he ac ha he ange o ha diness dec eases wi h he minimum empe a u e in he coldes mon h. These esul s sugges he e is a ade-o be ween species ha ole a e shade and hose ha ha e conspicuous lowe s, as well as wi h hose ha ha e highe ha diness alues. We expec ed ha di e ences ac oss pa ks be ween he p opo ion o Fig. 2. Rela ionship o i e plan ai s o (A) he minimum empe a u e in he coldes mon h and (B) he annual ange o empe a u e. Gene alized linea models (GLMs) o plan ai s e sus minimum empe a u e in coldes mon h and annual ange o empe a u e. The con inuous ai a iables (i. e. minimum ha diness, maximum ha diness, ange o ha diness [scale 1–12], and shade ole ance [scale 1–5]) is shown on he main y axis (le side o he g aph), while he scale o he unique bina y ai a i- able (i.e. p esence o conspicuous lowe ), con e ed o p opo ion o species ha ing pe pa k, is shown on he seconda y y axis ( igh side). * 0.01 <p ≤0.05, ** 0.001 <p ≤0.01, *** p ≤0.001, o he wise non- signi ican . P- alues in Table 4. (Fo in e p e a ion o he e e ences o colou in his igu e legend, he eade is e e ed o he web e sion o his a icle). ´ A. Bay´ on e al.