Effects of connectivity on -dispersed forest communities in agriculture-dominated landscapes Cendrine Mony, Juliet Abadie, Assu Gil-Tena, Francoise Burel, Aude Ernoult

To cite this version:

Cendrine Mony, Juliet Abadie, Assu Gil-Tena, Francoise Burel, Aude Ernoult. Effects of connec- tivity on animal-dispersed forest plant communities in agriculture-dominated landscapes. Journal of Vegetation Science, Wiley, 2018, 29 (2), pp.167-178. ￿10.1111/jvs.12606￿. ￿hal-01806869￿

HAL Id: hal-01806869 https://hal-univ-rennes1.archives-ouvertes.fr/hal-01806869 Submitted on 21 Jun 2018

HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 km s (LTSER) Research Socio-Ecological Term Long Location Is dominated landscapes? effect this zoochorous dispersal modes? dependent on agriculture- of woodlots in assemblages plant animal-dispersed affect connectivity does How Questions Abstract Mony, C. Auteurs Connectivity forest plantassemblages animal-dispersed effects on headRunning Co Articletype : Research article CENDRINEDR. MONY(Orcid : ID 0000-0002-0061-6521) 3 2 France Cedex, : : : Research: RECOVER IRSTEA, Unit, 13182Aix- UMR CNRS ECOBIO, UniversityLeclerc,Avenue Rennes1, duGénéral of 35042Rennes InForest ResearchJoint Unit, CEMFOR, -ordinating Editor : Monika Wulf Accepted ArticleEffects 2 ), BrittanyFrance)(Western 1 , Abadie, J. of connectivity on animal-dispersed forest plant communitiesanimal-dispersed connectivityforest plant of on Corresponding Author [email protected] Id : 1,2 , Gil-Tena, A. Coordinating Editor: Dr. Monika Wulf dominated landscapes dominated landscapes 1,3 , Burel, F.

CTFC, 25280 Solsona, Spain CTFC, Spain 25280Solsona, 1 en ite , Ernoult, A. -Provence Cedex 5, France -Provence 5,France Cedex of “ Zone Atelier Armorique Atelier Zone 1 in agriculture-in

” (ca. 150 (ca. at different dispersal distances and woodlot size on the functional dispersal structure of the the of structure plant communityusing dispersal functional the on size woodlot and distances dispersal different at flux Dispersal Potential Total of Proportion of effects the analysed We ). zoochorous species and decrease in biodiversity (Brooks et al. 2002; Fahrig 2003 Fahrig 2002; al. et (Brooks biodiversity in decrease and extinction species in resulting often dynamics, plant of driver major a as considered is loss Introduction LTSERArmorique” “ZA p community, plant the of structure functional the shaping towards contribute size habitat in decrease and isolation habitat both that indicates study This of proportion the Conclusion and richness species dispersalshort at detected epizoochorous were effects These Connectivity woodlots. big of in area. assemblages in cover endozoochorous woodlot proportion and connectivity the between interactionincreased the by impacted were species endozoochorous and epizoochorous Both size. woodlot by influenced primarily was modes, zoochorous different the of species proportions zoochorous on influenced of Connectivity size. richness habitat ofwith increased community proportion the The within tested. distances dispersal of range the in size woodlot on depend only assemblages zoochorous plant overall that demonstrated We Results zoochorous of cover and richness species of zoochorous( modes proportion specific for assemblages and species these within the calculated We woodlots. of margins and core the in assemblages plant of composition the analysed We vectors). dispersal ( movement animal ( to permeability matrix landscape of function a as calculated metrics 1500 reachability to 100 from habitat distances dispersal using Landscape the woodlot in Flux Dispersal each Potential Total of of Proportion connectivity the assessed We matrix agricultural an in embedded woodlots post-agricultural small 26 sampled We Methods Key ofthecomposition community ofdispersalwith the whole set patterns. functional the recover to necessary is connectivity landscape of restoration thorough more a short preserve to sufficient be to seems surroundings woodland the long-distance in connectivity woodlot Maintaining size. landscapes habitat large needing species fragmented plant of rareness the these in of or movements animal that small-sized of selection the of because either suggest lost been has dispersal results Our mode. dispersal Accepted lant assemblages, , interactions, functional dispersalplant-animal traits, Article words: words:

distances. Our results were results distances.supported Our linear models. models. linear

(NW France) m. hs erc w metric This in both total and core plant assemblages. total andcore assemblages. in both plant xet o tedsocoos group, dyszoochorous the for except as u te at t ifrn lvl of levels different at act they but ae o gah theory, graph on based ) calculated along a range of of range a along calculated -distance dispersal though though dispersal -distance i.e ., ., epi-, endo epi-, i.e. ly zoochory, ; Helm et al. al. et Helm ; the relative the , plant seed , - - and was was and (1 and dys- and which which – 7 ha) i.e. . , 2004 Whigham 2004; Diekmann & Kolb 2003; al. et Verheyen production, seed low exhibit to tend species Such 2004). Whigham 2002 al. (Honnayet woodlots faraway or newlycolonize established beingto unable limited, dispersal- are forests in species plant Most 2000). al. et (Cain isolation of effects negative the for compensates strategy this because landscape, the in persistence their to contribute isolated . provid species forest the for remnant last the though offer woodlots landscapes, dominated agriculture In 2005). al. et Honnay 2005; Dieckmann & Kolb 2003; al. et Jacquemyn 2002; Ehrlen & Dupré 2000; decreasing by Sunde & Graae 2000; communities Eriksson& (Ehrlen specialists forest the for especially richness, species plant forest local of composition the impact negatively size the within embedded reduced and/or woodlots isolation habitat that demonstrated have studies Empirical isolated matrix. agricultural but numerous to conducting habitats forest of plantations increase to also tend 2080/92) Nº EEC (Regulation Policy Agricultural Common European the within promoted measures greening The 2012). Pereira & Navarro 2010; al. observed been have afforestation and encroachment shrub al. et (Jacquemyn destruction forest extensive with fragmentation, of history long a have Europe in Forests 1996). al. et (Young recolonization of likelihood the reduce hence and, isolation their promote distances inter-patch big while 1970) (Levins surfaces habitat small in extinct 2006 Smallwood 1982; Velle 1982; Smallwood & (Howe zoochory through transport by promoted mostly are and rare, are events dispersal 2002 Ehrlen & Dupré 1982; (Bierzychudek dispersal seed long-distance for adaptations

Accepted Article manyplaces 2003). in Nevertheless, ). Because of the reduced patch size, the have a higher probability of going going of probability higher a have populations the size, patch reduced the of Because Th e capacity for long-distance dispersal by plant species at the landscape scale may may scale landscape the at species plant by dispersal long-distance for capacity e nd et al. 2003 al. et ed they have the capacity to (re)colonize and establish in these in establish and (re)colonize to capacity the have they ). In fact, may serve animals Infact, ). of Western Europe, land abandonment and subsequent and abandonment Europe, land Western of since the 20 the since ). Consequently, long-distance long-distance Consequently, as important vectors for the the for vectors important n otnlc specific lack often and th century (Verburg et (Verburg century ; ; matd y h preblt o lnsae lmns o nml oeet (Bélisle movement animal to elements landscape of permeability the by impacted patch, source the to distance Euclidian and cover habitat of amount the of combination a as connectivity untouched. seed 2015 BurelLa et al. 2008; Point organisms of responses behavioural account into taking woodlots, of connectivity functional potential the assemblages zoochorous on connectivity of effect the expect would we sense, this In used. be must indices connectivity functional representative more Thus, 2003 al. et parent Haddad the from distance of behaviou animal by function affected be also simple may but a , not are patterns these fact, In species. H decreases. patches around surface forest when decreases species, forest core especially species, zoochorous of richness the that demonstrated Grashof-Bokdam (1997) dispersal. seed plant of probability the reducing potentially animals, of resources habitat among organisms of movement the impedes or facilitates landscape given a which to degree ( connectivity of lack However, patches. isolated between forest of dispersal Acceptedthat rangeshave home small dyszoochory, of case particular transport during them lose accidentally or winter system theanimal of ( fur; dispersal of type the on Article ) endozoochory, when are eaten and pass undamaged through the digestive digestive the through undamaged pass and eaten are seeds when endozoochory, ii) Vittoz & Engler (2007) reported four different categories of zoochorous species based based species zoochorous of categories different four reported (2007) Engler & Vittoz to hc mgt o cmltl rfet ed ipra pten i zoochorous in patterns dispersal seed reflect completely not might which landscape structure and elements (Tischendorf & Fahrig 2000; Kindlmann & Kindlmann 2000; Fahrig & (Tischendorf elements and structure landscape Myrmecochory usually contributes to short distance dispersal, distance short to contributes usually Myrmecochory ; Taylor et al. 1993) may also negatively affect the abundance and diversity diversity and abundance the affect negatively also may 1993) al. et Taylor Wl & akneg 08. hs ye f ipra behaviou dispersal of type This 2008). Tackenberg & Will ; ; ( iii : ) (i) epizoochory, (i) dyszoochory, when seeds are foraged by animals that store them for animals areforaged seeds thatstoredyszoochory, when by themfor are limited when the configuration of forest habitat is fragmented fragmented is configuration forest habitat when of are limited the in which ants generally eat seed elaisome but leave the rest of of rest the leave but elaisome seed eat generally ants which in ).

when seeds are transported passively by animals in in animals by passively transported are seeds when ; n ( and r (Nathan & Muller-Landau & (Nathan iv wvr ti suy considered study this owever, myrme ) to be rather explained by explained rather be co cho ry , which is a a is which , because ants ants because mgt be might r i.e., 2005 2000 the the ) ; . 200 Pascual-Hortal 1996 (Fukui short very be may birds in time retention gut fact, In birds. and rodents, , as such vectors, as animals small-sized investigated have gut and 2008 Tackenberg ingestion, & Will 2007; seed Engler & type, (Vittoz rates retention fur including attributes, of variety a on depend distances dispersal However, epizoochory. to compared endozoochory through propagation of distance longer to contribute to dispersers these suggest studies These 2005). al. et Cosyns 2004; al. has mammals, large on focused dispersal actual measuring literature existing The records. such perform to difficulty ( trapping seed or seeds marked using calculated are distances dispersal actual Such these modes. different through achieved are that distances dispersal actual the measured empirically have (>100 dispersal long-distance to contribute (M hoy acltd s fnto of function a as calculated theory Connectivity landscapes. agriculture-dominated of woodlots post-agricultural small in assemblages plant zoochorous the scale are dispersal thedifferent at which modes of sensitive is measurement indirect thresholds distance detect to help may This connectivity. functional of distances different at loss connectivity to groups dispersal plant these of response potential the assess to is distances dispersal actual measuring dyszoochory. investigated have studies fewer Even vectors. dispersal small-sized in endozoochory than dispersal long-distance to more contributes epizoochory

Accepted Article ü ller-Schneider 1983; De Sanctis et al. 2010). The three other zoochorous categories may may categories zoochorous other three The 2010). al. et Sanctis De 1983; ller-Schneider h peet td aim study present The e.g. , Tewksbury et al. 2002; Levey et al. 2005). Data are then scarce owing to the to owing scarce then are Data 2005). al. et Levey 2002; al. et Tewksbury 7 ). We only focused on long-distance dispersal (>100 m (>100 dispersal long-distance on focused only We cost wa and infer and including wild herbivores and cattle (Pakeman 2001; Couvreur et Couvreur 2001; (Pakeman cattle and herbivores wild including - s assessed through habitat reachability metrics based on graph graph on based metrics reachability habitat through assessed s effective ed to analyse how connectivity influences the structure of of structure the influences connectivity how analyse to adcp preblt t aia mvmn (ar & (Saura movement animal to permeability landscape potential (Calabrese & Fagan, 2004) 2004) Fagan, & (Calabrese m dispersal distances dispersal sensu Cain et al. 2000 al. et Cain ; Traveset 1998), Traveset ; .

). In contrast, fewer studies fewer contrast, In ). to each dispersal type dispersal each to and ). However, few studies few However, ).

could could An start sensu suggesting that suggesting alternative to to alternative

determin Cain et al. et Cain . This ing fertile more with sandstone on is soil north, the in whereas granite is bedrock soilIn south, the agriculturalpractices. of types characteristicsand soil partlyby driven south, T network. hedgerow well-developed (LT Research Socio-Ecological Long-Term the in out carried was study present The Study site Material Methods and hypotheses: myrme account into take not did and 2000), Accepted a with area, agriculture-dominated an by characterised is landscape The 2014). al. et Gil-Tena imagery(see aerial using satellite site and thesame photography aroundLTSER the extent the km 3 enlarged we 2007), Saura & (Pascual-Hortal assessment connectivity the in effects edge (48° France Western Brittany, “ of Article oe tle Armorique Atelier Zone (ii) (i)

responseendozoochorous to similar species. species. epizoochorous to compared distances shorter at loss connectivity to sensitive more be may species endozoochorous involved, are vectors size smaller if Alternatively, species. endozoochorous to compared connectivity in disruption large short-distance on through dependent more be achieved may species epizoochorous is mammals, dispersal if Specifically, manner. dependent distance- a in mode zoochorous of types different the affects Connectivity functionalpotential increasing with increase species zoochorous of richness and abundance The Because dyszoochory is based on a foraging behaviou foraging a on based is dyszoochory Because ”

( 36′ Bocage N, 1° 1° N, connectivity his hedgerow network increases in density from north to to north from density in increases network hedgerow his -countryside- research site), which is located in in located is which site), research -countryside- 32′ W), and cover and W), co of woodlots; hr. e pcfcly test specifically We chory.

s ca. 150 ca. km². In order to remove to order In km². ed soils than in the the in than soils h following the r, we expect we r, SER) site SER) a E satellite. RapidEye by classification aerial sensing remote and based object with combination in Information) Forest and Geographic of Institute National (French the potentialof habitatareaforest species. slightly have species. forest for friction matrix and woodlots parcels). isolate and hedgerows Policy have configuration site ofthe south inthe forest largeancient further 1 covary thesecoarse environmental scalewith atvariables. (see measures connectivity ( occurrence hedgerow land of type the conditions fertilitytherefore Soil south. dispersal of plants (Cain et al. 2000) whereas allowing to have a significant subset of of subset significant a have to allowing whereas 2000) al. et (Cain plants small-distance of to dispersal corresponds fairly because chosen was threshold distance aggregation wasInstitute produced by theFrenchNationalGeographicForestInformation. of and (2003 BDTopo® database geographic vector the from identified were and roads network hedgerow The roads. and grasslands, hedgerows bodies, managed water areas, grasslands, urban semi-natural woodlands, crops, resolution: m 5 at identified were ) .

Accepted Article Mo t f h wolns n h area the in woodlands the of st The land-use map was obtained from a photointerpretation of aerial photography photography aerial of photointerpretation a from obtained was map land-use The of colonization of context a in stands area study The odos lsr hn 5 wr cniee a blnig o h sm entity. same the to belonging as considered were m 25 than closer Woodlots spontaneous colonization by other plants and plants other by colonization spontaneous n te eutn cag i arclua patcs ( practices agricultural in change resulting the and hs lnsae modifications landscape These increased through mostly plantations of post of plantations mostly through increased been been tes cutt trees d i.e. occurr mr dne egrw ewr i te ot) n my c on act may and south) the in network hedgerow dense more , section ing

since the 1960s due to the to due 1960s the since n de o reparcelling to due ing

“Connectivity assessm “Connectivity

r cmoe o oiial patd odos with woodlots planted originally of composed are

(Fig. 1) (Fig. nrae te led eitn ioain f the of isolation existing already the increased In the same time, time, same the In . S trong modifications of agricultural trong modificationsmatrix of

natural succession natural - use and the and use

ent of woodlots”) of ent aadnet f es productive less of abandonment , - giutrl odos enhancing woodlots, agricultural European Common Agricultural Common European post e.g. - , agricultural

woodland woodland parcel nrae n acl size, parcel in increase ight land-use categories land-use ight . The area comprises a a comprises area The

size and hence the the hence and size

which may then may which

cover seems to seems cover – woodlots 2006), which which 2006),

This This (Fig.

(patch) ( ha 1 than larger woodlots and forests unsampled ( vectors landscape the in Flux Dispersal Potential the computed we woodlot target each For 2007). Pascual-Hortal & through connectivity woodlot computed We Connectivityof woodlots assessment lands or meadows) and by dominated trees, broadleaved of composed were woodlots sampled The A). Appendix 1; (Fig. area) the in woodlots the of median the is which 0.04 below ratio (edge:area compactness the high with is and area) the which in woodlots ha the of 2 size average to (close size similar with woodlots 26 selected and ratio) (edge:area shape and size woodlot calculated then We map. land-use the to according site LTSER the spatial the to according area photography. aerial the study of resolution the within (>1ha) sample to woodlands candidate Accepted remain the regarding woodlot that of proximity patch of connections forests and woodlots certain a (dF* Flux Dispersal dispersal plant seed of movement the flux dispersal as study this in considering specifically Article atna sativa Castanea k, dF* i.e. sampled , k animals).

is therefore woodlot (patch woodlot

mainlyduring the20thcentury k . These woodlots were established on former agricultural lands lands agricultural former on established were woodlots These . ) k is based on patch removal experiments and experiments removal patch on based is

n h lnsae [ landscape the in ih l ohr ace i te landscape the in patches other all with We considered as habitat patches the sampled woodlots woodlots sampled the patches habitat as considered We given by k ) :

the the Following this criteria, we detected 143 entities within entities 143 detected we criteria, this Following percentage of total of percentage ( LT dF* a S graph-theory based reachability metric (Saura (Saura metric reachability based graph-theory k R ie + k bfe area) buffer km (+3 site ER ; Saura & Rubio 2010; Gil-Tena et al. 2014) al. et Gil-Tena 2010; Rubio & Saura n hbtt patches) habitat ing and Fig. 1 Fig. had a ).

The potential similar Fagus sylvatica Fagus Proportion of Total Potential Total of Proportion

( was i.e.

extensive extensive dispersal flux dispersal , by accounting for the the for accounting by ,

.

computed F rprin f Total of Proportion or a given woodlot woodlot given a or , management Quercus robur Quercus ] through the the through ] to assess to

among all among n the and (arable (arable for . ,

p woodlot each between distances. euclidian on based than vectors)rather ( movement animal the to resistance matrix the and permeability references& Sauratherein 2007 Pascual-Hortal 2007). Hortal (Saura patches two the between dispersal stones) stepping as functioning patches and where resistance to movement) to resistance fragmented in species woodland f (2010), by attributed those on based were and (2014) al. et Gil-Tena by area study the for parameterized w in m 1 moving than dispersal plant seed the ( vectors for say, to is that B); (Appendix areas urban for 50 of threshold friction maximum a and ha 1 than larger woodlots forests for one of value friction minimum with function exponential mathematical a to corresponded distribution value Friction 2010). al. et (Watts species woodland forest of movement the for permeability their to according them classifying through categories land-use the from obtained cartography) movement for woodlots among distance dispersal the of function exponential negative a as dF at e al. et Watts

Accepted Article k * j i te adcp, nldn drc ad o-iet fclttd y te intermediate other by (facilitated non-direct and direct including landscape, the in ,  p In this study we considered inter-patch dispersal distances dispersal inter-patch considered we study this In   i ij   n i.e. * ,1 1 riction values values riction  n

,1  is the maximum product probability of all possible paths between two patches, two between paths possible all of probability product maximum the is 1  , animals) moving one meter distance in urban areas is fifty times more difficult difficult more times fifty is areas urban in distance meter one moving animals) , n kii p The probability of direct dispersal among woodlots woodlots among dispersal direct of probability The ik * jij p (2010 ij * )

s a as air was calculated was air were olns n frss 1 ha 1 ≥ forests and oodlands along the least cost path by the Graphab 1.0 software (Foltête et al. al. et (Foltête software 1.0 Graphab the by path cost least the along ucin of function salse bsd n xet rtra n fcsn o generic on focusing and criteria expert on based established countryside countryside

h vria srcue f h habitat the of structure vertical the from the friction map friction the from adcps n UK in landscapes ).

We used a friction map ( map friction usedWe a . The friction values were previously previously were values friction The . as the accumulated cost accumulated the as . i

and n u study our In as i.e. a function of landscape of function a j , ( ln se dispersal seed plant p i.e. ij ) , impedance/cost . is here modelled here is n at e al. et Watts In , the distance distance the , i and & Pascual- j ( (see i.e. i ,

25 leastatat and woodlot the of centre the to closelocated W surveysFloristic &Conefor (Saura Torné 2.6 at function exponential negative the of rate Each 2014). al. et distance dispersal potential “modified” Gil-Tena 2011; al. et (Gurrutxaga area buffer km 3 + site LTSER the in friction of value median statistical the by multiplied was distance dispersal potential Each a community of thresholds resolution functional fine-grain for detect to enable may connectivity assess to distances of range large a on based approach multiscale This types. zoochorous on depending connectivity functional characterise to distance relevant most the determine to intervals) m 100 at 1500m to m 100 (fromdistances dispersal potential planarconnectivity withminimum graph calculated are indices completegraph correlated. or A) (Appendix pair patch each among paths cost least these compute to graph planar minimum a selected We 2003). al. et Adriaensen 2012; (in percentage cover) for two vegetation layers: shrubs and herbaceaous plant species. Ferns species. plant herbaceaous and shrubs layers: vegetation two for cover) percentage (in abundance and composition species plant assessing by surveys floristic performed We area. margin the in located were plots three and area core the in located were plots three design: 5 × 14 six selected we woodlot, each For sizes. small woodlot the of because effects edge by affected are woodlot the of centre the at assemblages th on based arbitrarily 25m-value this fixed we considered, literature organisms the or environmental in of reported set the effect on edge depending for values possible of range large the of Because

Acceptede Article sampled each woodlot in the core and margin areas. The core area was defined as the area the as defined was area core The areas. margin and core the in woodlot each sampled We calculated the percentage of dispersal flux for each woodlot (dF woodlot each for flux dispersal of percentage the calculated We e ie ag o sts osdrd W cno teeoe xld that exclude therefore cannot We considered. sites of range size 2009). 2009). by the median friction value was used to set the decay the set to used was value friction median the by p ij = 0.5. These calculations were made using using made were calculations These 0.5. = as Gil-Tena et al. (2014) demonstrated that that demonstrated (2014) al. et Gil-Tena as

m m from the border (Matlack1993). the from m plots using a systematic sampling systematic a using plots ssemblage responses. responses. ssemblage k *) using fifteen using *) Rameau et al. ( species forest as considered not were they because cover” as relative to “zoochorous (referred assemblage and plant richness” total relative and “zoochorous core the over proportions their and cover, woodlots), ( plots sampling the over cover of percentage pool species For endozoochorous, other. or epizoochorous, typology: dyszoochorous, following the using species each of vector dispersal primary the using assessed were traits Dispersal Assessment traits dispersal of 140 differs layer, mode dispersal their because account do and angiosperms into taken not were mosses and Accepted dys- species zoochorous over species epi-zoochorous and dys- endo-, of cover) and richness species (in proportion assemblage”) centr the at both located plots or assemblage”) vector, dispersal of type each and woodlot ( used was habitat same the in growing relatives Article , epizoochorous cover” relative , species pool recorded, recorded, species pool due to its dependence on the initial planting and management of the woodlot. From the From woodlot. the of management and planting initial the on dependence its to due either considering only plots located at the centre centre the at located plots only considering either ) . We analys We where data were not available at the species level, species the at available not were data where 1994 ). ). (referred to as “endo as to (referred es not rely on zoochory. We did not analyse the composition of the tree the of composition the analyse not did We zoochory. on rely not ed 11 the effect of connectivity on (i) zoochorous species richness and and richness species zoochorous (i) on connectivity of effect the

in forest fragmentin forest communities species (nine species , respectively). , respectively). -, d -, Baseflor we calculated the total number of species and the and species of number total the calculated we herbaceous and two herbaceous and ys i.e., a - , epizoochorous relative richness” and “endo and richness” relative epizoochorous , few cases (<5 species (<5 cases few e.g., mean percentage cover over the plots of the of plots the over cover percentage mean ad h margin the and e aaae Jle 05. e eetd the selected We 2015). (Julve database

Rumex i.e., listed in the French Forest flora, flora, Forest French the in listed or

shrub species) were discarded werediscarded shrub species) Epilobium the dispersal mode of close close of mode dispersal the respectively) , f h wolt (“core woodlot the of , of the woodlot (“total (“total woodlot the of ~4 % of the analysed the of % ~4 species). For each each For species). ; ( ii from from ) the - , for Foundation (R software 2.15.3. R using performed were tests statistical All ANOVAs. by assessed was model the in variable explanatory each of significance The models. these in (Arnold AICc lowest the with model the our In with those as (AICc). models supported most sizes the selected we sample analyses, small for corrected AIC second-order using variable each (AIC) criterion information Akaike’s on based selection variable explanatory for procedure selection stepwise backward a using optimised 15 producing intervals), m 100 at m, explanatory as area addition, In woodlot variables. and metrics connectivity with regressions linear multiple plant the on connectivity of effect the for test To measured index. Sorensen using additionally was assemblages edge and core between Similarity species. zoochorous of cover species and number species for except variables all for 0.9 than lower were correlations but assemblages total and core between correlated total significantly and were indexes core All between assemblages. correlated were indexes these which to degree the analysed also a core), and (total assemblage correlations) (Pearson ecological correlations pair-wise the through between studied independence variables for checked we analyses, our conducting Before S the proportion of the proportion of the of (10 distance each normality for developed was model the One residuals. model of improve distribution to log-transformed were data index the necessary, When their considering through size patch by mediated was connectivity woodland Accepted Article analyses tatistical trait variation that was accounted for by the coefficient of determination of coefficient by the for accounted that was variation trait we check ll plant ed hte te omnt rsos o frs plan forest of response community the whether -dispersal assemblage indexes were independent. We We independent. were indexes assemblage -dispersal models per response variable, with each one being being one each with variable, response per models 2010 ). We calculated the regression coefficients and and coefficients regression the calculated We ). W cmae tee piie mdl for models optimized these compared We . dsesl sebae nee, e used we indexes, assemblage -dispersal Δ i[AICc] within within i[AICc] . Inside each plant plant each Inside 0 interaction. interaction. m to 1500 to m ≤ 2 units of units 2 ts to to ts ( R² ) ) increased assemblage the in species zoochorous of proportion the area: woodlot on dependent was species of richness relative The 2). (Table assemblages core or total regardless the within assemblages, species of majority the represent species Zoochorous 1). (Table assemblages] ( [mean species zoochorous for 0.89 to 0.38 from and species total for 0.84 to 0.31 from varied assemblages core and edge between 4 10 from contained level woodlot the at assemblages plant Forest woodlot oftheCharacteristics assemblages Results packages AICmodavg the through Austria) Vienna, Computing, Statistical 2 Fig. assemblage, core for effect marginal assemblage, total for effect (significant size woodlot dependentcover relativewere not and Species richness, cover Effect connectivity of mode, dispersal dominant followed and dyszoochorous by epizoochorous types. the was dispersal type endozoochorous species, zoochorous species), forest of ). 7 and 1 and Accepted Article 87 % percentage cover (Table 1). Sorensen index calculated for assessing similarity similarity assessing for calculated index Sorensen 1). (Table cover percentage % . . either in richness (44.19 richness in either ih lre ag o vrain mn wolt (al 1). (Table woodlots among variation of range large a with and woodlot area area woodlot and to 90.91 to SD on zoochorous species on zoochorous species ): 0.59 ): % of forest species) or cover (48 cover or species) forest of % (0 .10 ) for total; 0.67 (0.10 0.67 total; for ) on connectivity or woodlot area area connectivitywoodlot or on to 43 species, with between with species, 43 to Effec t, t, HH ) for zoochorous for ) . , 96 MASS to 99. to Within with and and 75 % a relativelyR² high regardless the assemblage connectivitysmallest distance on effect positive marginally a had connectivity addition, In assemblages. core and total woodlot for both species, dyszoochorous 200 woodlots small in connectivity with decreased assemblages. core and total woodlot the for both richness relative their on area and connectivity between effect 3 (Fig. woodlots bigincreased in but woodlots, small in connectivity with coverdecreased plant an on dependent the in was species endozoochorous of proportion The scale 3). (Table factors both of assemblage effect interactive total woodlot the at species endozoochorous assemblages core and total in species endozoochorous W the dispersalmodesEffect connectivityof relative of of proportion the on from and phenomenon ). This effect was only detected for connectivity calculated at a short distance of 100 m, 100 of distance short a at calculated connectivity for detected only waseffect This ).

Accepted Articlee

m on ta wolt ra n/r onciiy i nt fet h rltv rcns of richness relative the affect not did connectivity and/or area woodlot that found

in We detected no effect on the relative cover of epizoochorous species but an interactive an but species epizoochorous of cover relative the on effect no detected We We observed a significant positive effect of woodlot area on the relative richness of richness relative the on area woodlot of effect positive significant a observed We both types ofassemblage 100 was detected for a connecti a for detected was

to 2 elative richness of epizoochorous species epizoochorous of richness relative The 00

of 0.26. of 0.26.

m

for core assemblages core for being This effect was not detected in core assemblages. This effectwas core assemblages. detected in not tested considered. .

(100 (100 pce rltv rcns fr oa assemblage total for richness relative species vity m) . Relative cover was. Relative

distance of 100 to 300 to 100 of distance .

T he ,

highest but increased in big big in increased but . oee, h rltv cvr of cover relative the However, R ² (0.21 in in dependent on both factors, factors, onboth dependent

zoochorous assemblages zoochorous – m 0.23)

for total assemblages total for zoochorous species zoochorous species was woodlots

obtained for obtained .

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Accepted Article particular of selection the in involved be may size) seed as (such traits certain instance, r vrl, hs td sget that, suggests study this Overall, io u o aias Te fet f slto o dsesl taey f plant of strategy dispersal on isolation of effect The animals. of r n giutr-oiae lnsae, long-distance landscapes, agriculture-dominated in calling for increased research efforts efforts research increased for calling in endozoochory and endozoochory the surroundings of woodlots is woodlots of surroundings the to particular groups particular dyszoochory. Bélisle, 2010 T.W. Arnold, species invasive of spread the Modeling 2014. M.C. Fitzpatrick, & E.L. Preisser, J., Ferrari, herbs. forest in occupancy patch and limitation Dispersal 2000. O., Eriksson, & J. Ehrlen, Couvreur, 2005 M. Hoffmann, & I. Lamoot, S., Claerbout, E., Cosyns, plant in dispersal seed Long-distance 2000. A.E. Strand, & B.G. Milligan, M.L., Cain, A.B., Rulands, G.A.B., Fonesca, da C.G., Mittermeier, R.A., Mittermeier, T.M., Brooks, forest temperate shade-tolerant of demography and histories Life 1982. P. Bierzychudek, 2015. M. Vellend, & H. Calster, Van K., Verheyen, T.J., Davies, L., Baeten, & H. Gulinck, S., Villalba, E., Swinnen, G., Blust, De J.P., Chardon, F., Adriaensen, References Economy andCompetitiveness of Ministry Spanish the by funded was Gil-Tena A. funding). (CNRS Pleine-Fougères of sites agricoles paysages les dans project Agriconnect - 3 (DIVA Agriculture of Ministry French the by funded was work This GEOSUD. by provided was imagery RapidEye comments. valuable Fahrig, L. 2003. Effects of on biodiversity. on fragmentation habitat of Effects 2003. L. Fahrig, hypothesis. amount habitat the effects: isolation and size patch Rethinking 2013. L. Fahrig, Ehrlén, & C. Dupré, 2010. F. Bruno, & F. Francesconi, F., Attorre, M., Alfò, M. Sanctis, De 2004. W.F. Fagan, & J.M., Calabrese, of Ecology plants. understorey forest of capacity colonization the in phylogenyfrom dispersal Information Criterion. model. usingmodels. dynamic network Ecology assessment by and inaspatially cattle horse heterogeneouslandscape. populations. 923. 2002 C. biodiversity. of Hilton-Taylor, hotpsots the & in extinction G. and loss Magin, Habitat S., Olfield, J., Pilgrim, P., Flick, W.R., Konstant, herbs: a review. ecology. 2003 E. Matthysen, Journal ofEcology EcologyFrontiers in andthe Environment AcceptedEvolution andSystematics Journal ofBiogeography near Rome in distribution and richness species on quality and configuration Article M.

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* *

Area We did We did 2.90 3.23

Accepted Article Relative cover Relative richness Dyszoochorous Relative cover Relative richness Epizoochorous Relative cover Relative richness Endozoochorous Core assemblage Relative cover Relative richness Dyszoochorous Relative cover Relative richness Epizoochorous Relative cover Relative richness Endozoochorous Total are bold significant. Models in as relativeassemblage.zoochorous to 3: coverthe differentMost totheTable zoochorous supportedmodels Richness and are AIC for framework types. according Accepted Article assemblage

Dist 200 100 200 100 300 100 300 100 ------ance

m m m m m m m m

G ener 0.0045 - - - 0.002 0.002 0.21 0.16 0.19 0.21 0.10 0.13 0.22 0.03 0.19 0.17 0.23 0.26 0.13 0.04 R² al Model

0.71 0.01 0.34 0.08 0.06 0.04 0.30 0.34 0.12 0.04 0.02 0.20 0.06 0.07 0.04 0.02 0.11 p

Intercept 16.56 56.46 46.39 56.81 14.23 13.44 59.47 47.30 57.47 82.08

7.82* 4.86* 5.41* 2.11 2.17 2.25 1.23 1.20 1.29 2.53 F ***: p

Area < Estimate

0.001, **: p 0.001, **: p ------10.81 1.40 0.91 7.60 8.40 5.47 10.7 8.03 0.04 3.4

0.0003 3.68 t 0.89 0.15 0.84 1.60 1.26 0.18 < 0.01; *: p < 0.01; *:p F Connectivity

Estimate ------135.41 152.04 137.31 14.60 - 136.3 118.5 98.43 1.10 <

0.05; t:

8.96** 5.74* 5.68* 7.44* 6.65* 5.23* 7.71* p p F < Interaction

0.1. 0.1.

Estimate 40.02 32.91 23.49 32.88 38.2 29.8 0.30

expressed expressed

Accepted Article Accepted Article a size over 1 - LTSER Figure site the Map study of 1: enlarged with a 3 ha and in black those sampled sites black in and ha km buffer). km buffer). ( Armorique We show in gray all the gray all habitats in woodland with We show

Long-Term Socio-Ecological Research –

Accepted Article assemblages. area woodlot of Figure Effect 2:

on zoochorous on relative richness for for total and coreand Accepted Article size.woodlot lowest the of value highest values: the and size, traits woodlot of value on (mean) average the effects size, woodlot of interaction value the plot to chosen were size woodlot of levels Three assemblages. total for species dyszoochorous on area woodlot of and species Figure3 : Interactive effect of connectivity and woodlot area on endo- endo- onarea woodlot and connectivity of effect Interactive and epizoochorous and Accepted Article neighboring patches canbelinked). tothe sampledcorresponding according graph toa and planar ( woodlots and sampled black) gray the and in linksorpotential woodlots connections thehabitatsFigure woodlands in area of thein Representation study (woodland A.1: APPENDIX A

i.e. , only , only 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 identificator woodlot Sampled Figure (Seeconnectivit y analysis B.1). area. distances thegraph Euclidean on planar wereused calculated to based compute distances theEuclidean of relative sampled the to woodlots study thein woodlots other A.1. Table

Accepted Article

Sampled areaand woodlot interpatch shape descriptive and statistics of

4.69 3.60 2.99 1.44 1.49 3.35 1.17 3.67 1.13 4.84 4.97 6.60 4.44 1.17 8.00 1.66 1.54 1.78 Area (ha) characteristics Sampled woodlot 1.14 1.06 3.43 2.86 2.34 1.85 1.37

0.04 0.04 0.03 0.02 0.03 0.04 0.04 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.02 0.04 0.02 0.02 0.02 0.03 0.04 0.03 0.04 0.04 0.04 Shape

3 7 6 7 5 5 6 woodlo neighboring # of Sampled woodlot context 7 6 7 6 5 5 5 4 4 6 4 4 5 4 4 2 5 4

ts

67.08 330.15 190.00 199.25 113.14 340.59 151.33 min Distance (m) 390.51 191.05 205.91 560.80 405.22 782.94 308.71 130.00 60.00 70.00 331.06 214.71 138.92 10.00 220.23 72.80 546.72 164.01

320.16 962.60 1067.05 893.20 1082.31 1325.63 1494.52 max 1644.69 1287.63 2041.30 1559.55 892.02 1201.04 852.12 834.39 463.25 980.20 820.24 487.54 844.81 762.43 575.85 160.00 1686.56 593.63

157.56 657.95 659.56 544.13 627.88 800.06 773.33 mean 1096.74 773.45 1126.95 998.83 672.90 958.52 496.56 504.09 194.12 476.23 577.17 352.06 441.97 442.48 458.42 116.40 932.24 389.89

function exponential 50. with amaximum of threshold friction theon vertical B1.Decreasing toTable modelmatrix used values friction landscape based permeability APPENDIX B 26 Artificial lands (urban areas and roads) bodiesWater and watercourses Crops Semi Hedgerows woodlands and < 1ha Woodlands and forests 1 ≥ ha Land

Accepted Article - - natural andmanagednatural use

structure of the land uses(see the toan Watts land also of etstructure al.2010)according 1.82

grasslands

0.03

50 18.40 18.40 6.84 2.57 1 Friction value

5

530.38

1065.69

794.50