Standardized response signatures of functional traits pinpoint limiting ecological filters during the migration of forest plant species into wooded corridors

Ecological Indicators 108 (2020) 105688

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Standardized response signatures of functional traits pinpoint limiting ecological filters during the migration of forest plant species into wooded corridors Taavi Paal, Kristjan Zobel, Jaan Liira

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Institute of Ecology and Earth Sciences, University of Tartu, Lai 40, 51005 Tartu, Estonia

A R T I C LE I N FO

A B S T R A C T

Keywords: Ancient forest species Efficiency indicators Ellenberg indicator values Functional traits Patch-corridor-matrix system Rural landscape Trait convergence Trait divergence

Tree-lines and alleys are expected to operate as migration enhancing corridors for habitat-demanding species, but their functionality is limited by the set of ecological filters. We use multiple plant traits related to dispersal and establishment to identify the limiting filters for forest plants in the rural landscape of Estonia. We develop a set of quantitative metrics to rank indicator traits according to their distributional changes along migration distance. We implement a trait comparison to the potential optimum level suggested by two ecological reference groups of species to interpret these responses as filter driven convergence or divergence. The suggested set of metrics provided a clear ranking of traits and showed interpretational limitations of widely used short list of traits (e.g. seed weight, plant height and SLA). Results also demonstrate that there is no consistency between indicator metrics based on the shift in trait mean and those based on the reduction of variability, instead they provide complementary information. Unexpectedly, many characteristic traits of forest-specialist plants do not exhibit the expected responses. The response signal of many dispersal traits is too ambiguous to interpret because either (1) they do not have one clear optimum level, or (2) they indicate an establishment/persistence limitation instead, such as seed weight and flowering duration. Establishment traits indicate filtering clearly by improved light conditions. The pattern of trait means demonstrates that the dispersal filtering incrementally intensifies with distance, while establishment filtering occurs sharply at the forest-corridor ecotone. Consolidated results underscore that the migration of forest-restricted plants into corridors is limited by the habitat quality for dispersal vectors (e.g., for myrmecochores and zoochores), the scarcity of suitable microsites for seedling establishment, and the competition for light. A single optimal structure of wooded corridors cannot be suggested as forest-dwelling species exhibit various adaptations. Forest-biodiversity-enhancing wooded corridors should incorporate a diversity of shade levels and have structures that facilitate visits of forest insects, birds and mammals. We show that biased conclusions about the functional efficiency of habitats and limiting ecological filters can be avoided when indicator analytics include (1) multiple response metrics and analytical methods, (2) multiple seemingly redundant traits, and (3) several reference groups for interpretation. The proposed analytical approach adjusts for (1) the indictor choice subjectivity, and (2) the scaling bias implemented in several ecological indicator trait systems, which over-emphasise qualitative preferences of species rather than reflect their real niches.

1. Introduction Linear green infrastructure, consisting of hedgerows and alleys, is a traditional component of the European rural landscape, structuring fields, providing aesthetic enrichment and dispersal corridors for habitat demanding species (van Dorp and Opdam, 1987; Baudry et al.,

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2000; EEA, 2011). However, the function of corridors as a dispersalenhancing stepping-stone network seems to have limited efficacy (Beier and Noss, 1998; Davies and Pullin, 2007; Gilbert-Norton et al., 2010). For instance, only some forest specialist plant species have been found using corridors for dispersal to a considerable extent (Sitzia, 2007; Wehling and Diekmann, 2009b; Liira et al., 2012; Paal et al., 2017) and

Corresponding author. E-mail addresses: [email protected] (T. Paal), [email protected] (K. Zobel), [email protected] (J. Liira).

https://doi.org/10.1016/j.ecolind.2019.105688 Received 8 March 2018; Received in revised form 19 August 2019; Accepted 30 August 2019 Available online 18 September 2019 1470-160X/ © 2019 Elsevier Ltd. All rights reserved.

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1995; Laughlin, 2014). Approaches using traits make cross-confirmation of filtering possible and allow the pinpointing of specific filtering processes (Deckers et al., 2004; Vallet et al., 2010; Naaf and Wulf, 2011; Lõhmus et al., 2014). Problems arise from various simplifications in methods, for example, when one uses two or more inter-mixed types of indicators with different sensitivities – e.g., functional traits and habitat structure (Honnay et al., 1999; Deckers et al., 2004; Wehling and Diekmann, 2009b; De Sanctis et al., 2010; Liira and Paal, 2013). Also, the use of an intensively optimized list of indicator traits (e.g., the leafheight-seed system or LHS-system of Westoby (1998)) can result in inconclusive or biased interpretation because each single trait can indicate multiple ecological functions (Violle et al., 2007); e.g., seed size indicates both dispersal ability and establishment support, and plant height indicates competitive ability as well as seed release height (Weiher et al., 1999; Moles and Westoby, 2004; Thomson, et al., 2011; Brunet et al., 2012). The alternative use of intraspecific trait variability or demographic structures as indicators (Beier and Noss, 1998; Laughlin, 2014) have particularly low extrapolation potential as these methods can address only a few traits and species (Whigham, 2004; Violle et al., 2012; Gilbert-Norton et al., 2010; Loranger et al., 2016). Finally, the importance of ecological filters is usually interpreted qualitatively, based on the results of statistical comparisons of trait distribution metrics between the source and the recipient systems (Beier and Noss, 1998; Mayfield et al., 2010; Valdés et al., 2015). Distribution change is estimated either as a shift in the mean or a reduction in the variability of a trait (Weiher and Kedd, 1995; Violle et al., 2012); however, only the trait mean pinpoints a habitat condition that could be changed through management practices. Statistically quantified interpretations of trait distribution signatures are quite rare for a reason (McCollin et al., 2000; De Keersmaeker et al., 2011; Lõhmus et al., 2014; Loranger et al., 2016) – usually optimum trait values for a particular habitat are not quantitatively known or have little empirical support. As a result, misinterpretations on the ecological meaning of filtering are difficult to avoid. The objective baseline value of an indicator trait should be estimated from the group(s) of wellperforming species in the recipient habitat (Lavorel et al., 1997; Aavik et al., 2008; Liira et al., 2008; Liira and Paal, 2013). The use of two or more reference groups would reduce the subjectivity caused by the outgroup selection (Lõhmus et al., 2014), but the group ecologically nearest to the species of interest should be preferred. Using a comparison group, the trait change between habitats can be considered as either a functional convergence with, or a divergence from, that value set by the reference species group (Weiher and Kedd, 1995; Fukami et al., 2005). Trait convergence is expected to occur when species of both groups are limited by the same set of conditions. Trait divergence in the target habitat refers either to niche partitioning between functional groups or to the utilization of an unused niche by existing species, both leading to the coexistence of species or their functional groups (Macarthur and Levins, 1967; Stubbs and Bastow, 2004; Violle et al., 2007; Mason et al., 2012). Therefore, used in combination to assess ecological filtering, the shift in the trait mean should be used as the primary metric and the reduction in variability as a filtering confirming metric. We propose here a set of statistically supported metrics of trait distribution signatures for indicating the limiting ecological filters between the source and target habitat. We define the trait distributional signature as the systematic change of a trait mean and/or variability along the distance gradient. We propose analytical metrics evaluating the consistency of change in the indicator trait mean value and the change in trait variability. In the case of a mean value, we also propose an automatic interpretation of test results by using built-in conditioning against the trait reference value, which is observed at another ecological group species successfully established in corridors. We postulate that the strongest proof of trait-based filtering would be consistent support by all various analytical metrics. If only some of them show statistically significant results, we would consider this a partial

the island biogeography-type dynamics between forest patches prevail (Jacquemyn et al., 2003; Brunet, 2007; Lõhmus et al., 2013). The biodiversity supporting functionality of green corridors is limited by ecological filters of dispersal and establishment (Keddy, 1992; GilbertNorton et al., 2010; Staley et al., 2013). The debate over the relative importance of dispersal limitation and establishment limitation stems partly from methodological reasons (Beier and Noss, 1998; GilbertNorton et al., 2010) as the assessment methods applied to elucidate ecological filters vary greatly among studies (Lavorel et al., 1997; Violle et al., 2007). These methodological reasons include (1) the objective definition of a target group of species, (2) the filter-optimised survey set-up, (3) the selection of a comprehensive set of indicators, and (4) the choice of the analytical metric. Here, we propose an all-inclusive methodological solution consisting of survey set-up, indicator-set selection, and a set of quantitative intensity metrics. We use a case example of forest species to test the method for extracting the limiting ecological filters. First of all, the successful detection of limiting filters depends on the optimal delineation of the species group of research interest. Expertdefined habitat-specialist classifications can reduce the power of analyses because they include species with different habitat specialization levels and contrasting regional abundances (Beier and Noss, 1998; Hermy et al., 1999; Deckers et al., 2004; Endels et al., 2007; Schmidt et al., 2011). Functional groups defined by the composition of traits (Verheyen et al., 2003; Kolb and Diekmann, 2005; Roy and de Blois, 2006) tend to lead to tautological reasoning in the trait-filtering analysis. Therefore, we suggest that the research on ecological filtering should focus on common species in the regional meta-pool of species (Zobel, 1997; Cornell and Harrison, 2014; Suija and Liira, 2017), delimited by the specific empirical profile of habitat use in the region and by an ecological response profile closely related to the main problem of interest (Lavorel et al., 1997). There are various examples of applying such emergent group classifications (Beier and Noss, 1998; Dupré and Ehrlén, 2002; Aavik et al., 2008; Vallet et al., 2010), but in the present case we are interested in species that are forest-specific and have a colonization limitation in corridors (Liira and Paal, 2013). The second problem lies in the survey set-up, which should consider the specificity of all processes of interest. Migration is a hierarchical process, which consists of a dispersal step and an establishment step (Keddy, 1992; Zobel, 1997; Reid and Holl, 2013), but the dispersal event becomes visible only after the successful establishment of a species (McCollin et al., 2000; Paal et al., 2017). The simplifying assumptions about the sufficient environmental conditions in recipient habitats is hard to validate (Sitzia, 2007; Wehling and Diekmann, 2009b; Liira and Paal, 2013), because the effect of habitat quality is detectable only after the long-term accumulation of species (Adkison and Gleeson, 2004; Graves et al., 2006; Vallet et al., 2010; Liira et al., 2012, 2104). Therefore, we implement a study design that simultaneously addresses both dispersal and establishment filters with balanced emphasis. An optimal landscape configuration should consist of a well-connected source-target system. In such a system, establishment filters could be assessed even in the early stages of species accumulation, and dispersal filters could be simultaneously assessed by observing species occurrence continuously over a span of distance. For example, such a transect design running from forest to an attached corridor or recently planted stand has been used to survey the migration of forest plants (Corbit et al., 1999; Wehling and Diekmann, 2009b; Brunet et al., 2012; Liira and Paal, 2013). Ecological filtering can be estimated by contrasting filter-facing trait distributions (i.e., distribution signature) between a set of species in the source habitat (i.e., in species pool) and a subset of species in the recipient habitat (Keddy, 1992; Lavorel et al., 1997; Graae and Sunde, 2000; Wehling and Diekmann, 2009a). Objective interpretation and ranking of filters can be undertaken only when addressing a comprehensive set of multiple and partly functionally overlapping (i.e., functionally redundant) indicators of the same type (Weiher and Kedd, 2

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indication of trait filtration with additional evaluation needed. With the objective to improve the biodiversity-supporting function of wooded corridors, we address the question of why some forest plant species are restricted to forests and poorly utilize wooded corridors. We hypothesise that both dispersal and establishment filters limit the species and that filter emphasis has been biased towards dispersal limitation for methodological reasons. We use multiple functional traits, various analytical methods and a double reference system to reduce the interpretation subjectivity caused by trait and reference group selection.

20 m (Liira and Paal, 2013). In previous papers, we address the effect of habitat and landscape properties on the species richness and the composition of the herb layer along the gradient from the forest to the corridor (Liira and Paal, 2013; Paal et al., 2017). There we also show that the species richness of forest specialists decreases with distance along the corridor in a few tens of metres out of the forest (analogous to Sitzia (2007) and Wehling and Diekmann (2009b)) and that the main critical properties for forest plants overlap between the forest and the corridor, including disturbances. Therefore, in the present analysis, we consider the variability caused by corridor properties as additional natural noise in survey data.

2. Materials and methods

2.2. Sampling

2.1. Study region and sample sites

The study samples are from the summers (i.e., late May to early August) of 2009, 2010 and 2012 to account for both spring ephemerals and mid-summer species. The species sampling design emphasise recording the colonization success of forest species in corridors, which is recorded as species presence-absence events at different distances along the corridor (Fig. S1). The use of species abundance has little extra value or can cause bias for multiple reasons. First, the colonization events of forest-restricted species in corridors are rare enough for the data matrix to be zero-inflated. Moreover, biased noise is added into the abundance weighted trait means by the species-specific properties, such as post-establishment expansion and seasonal peak of abundance. Finally, weighting with abundance cannot be used to estimate trait variability. The transect consists of seven distance steps (Fig. S1). One is a combined relevé sample in the forest interior and along the forest edge, which represents the local species pool in the source forest. Other six sampling steps are positioned to represent the dispersal recipient corridor sections positioned at approximately exponentially increasing distances from the forest edge (5, 10, 15, 25, 50 and 100 m; Fig. S1). The increasing distance step accounts for the species colonization probability which decreases nonlinearly with distance from the source habitat (Honnay et al., 2002; Wehling and Diekmann, 2009a,b; Brunet et al., 2012). In forest interiors, the occurrences of all herb layer plants within a 100 m2 circular plot, located at least 20 m from the forest edge, are recorded (Fig. S1). Additional species are sampled from the forest edge of the corridor’s attachment within the range of the forest edge transitional zone, i.e. a plot up to five metres left and right from the central attachment point of the corridor and with a width of two metres into the stand, while avoiding conditions with open canopy or a recognizable forest interior. Such a large sample area has been implemented in earlier studies as it facilitates the inclusion of all potential forest plants in the source habitat (Corbit et al., 1999; Sitzia, 2007; Wehling and Diekmann, 2009a,b). At each of the six distance steps along the corridor, species are recorded from the plot with an area defined by two metres in length and five metres in width, except where the corridor width under the tree canopies is limited. As both the forest and corridor could contain drainage ditches constructed to remove excess water during wet seasons, only the species in the upper half of the ditch are recorded, to account for disturbed microhabitats created by ditch digging and to avoid hydrophytes or wet habitat species in ditch bottoms.

The study region is a 120 × 120 km2 area located in southeastern Estonia (centroid coordinates: 58°27′1″, 26°29′50″) in the hemiboreal vegetation zone of Northern Europe. The regional average annual precipitation varies between 600 and 700 mm year−1, and temperatures range from −5 to −7.5 °C in February to 16.5 to 17 °C in July (Metzger et al., 2005; Aunap, 2011). The flat terrain, which is 30–100 m above sea level, consists of a mosaic of various soil types: podzols, luvisols and gleysols, all suitable for nemoral and boreo-nemoral forests. A detailed description of the land use history of the region and a map of the study area are provided in our earlier paper (Liira and Paal, 2013). The interlinked forest-wooded corridor landscape complexes are selected according to strict predefined criteria (Table 1), which are described in more detail by Liira and Paal (2013). Most importantly, to ensure the well-formed and saturated local species pool, the source forest must be an ancient habitat, i.e., a forest with historical continuity on all historical maps. Also, the whole transect range (i.e., forest point and corridor sections) should be on the same soil type; for delineation we used the soil map of the Estonian Land Board (scale 1:10,000; xgis.maaamet.ee). To avoid pseudoreplication, neighbouring sites (i.e., distance at least 150 m) are selected only if they represent a contrasting structure of the corridor. Altogether, 50 forest-corridor transects meet all the criteria (Table 1). The tree layer of both forests and corridors is mostly dominated by deciduous trees, such as Alnus incana and Betula pendula. In corridors, the tree layer is dominated by Tilia spp.; other tree species formed some corridors or grow intermixed with Tilia. The main shrub layer species are A. incana, Salix spp., Prunus padus, Picea abies, and Sorbus aucuparia. The historical age of corridors ranges from 15 years to more than 110 years. The widths of the sampled corridors vary between 3.5 and Table 1 Criteria for transect selection. Criteria for a transect location: a continuously existing edge between forestland and open landscape, • Historically based on maps from 1888 to 1913 and 1907 to 1939, 1945 to 1952, 1978 to 1989, 1990 to 2000, and 2003–present day (maps from the Estonian Land Board)

present surrounding matrix habitat type is arable field or rotational grassland • The soil type is similar between the forest and corridor and is suitable for (boreo) • The nemoral species (soil maps of the Estonian Land Board, scale 1:10,000) the forest and the corridor consist of mainly deciduous trees; corridor can also • Both be formed by shrubs Criteria for a source forest: area 1 ha • Minimum continuous • Historically forestland trees are at least • Overstory 50 years old

2.3. Species classification

Criteria for a corridor: perpendicular to the forest • Orientation margin of at least 100 m • Length cannot be a forestland on • Location historic maps of at least one tree/shrub canopy • Width woody plant height: 2 m • Min canopy of woody vegetation • Continuous from forest to corridor

Overall, we record 272 herbaceous species and, on average, 60 species per transect, though the count ranges from 19 to 101 species among the sites. For patterns of small-scale richness, see Liira and Paal (2013) and Paal et al. (2017). The most frequent species recorded in the forest interiors are Dryopteris carthusiana (92% of forest interiors), Rubus idaeus (92%), Paris quadrifolia (90%), Oxalis acetosella (86%) and Fragaria vesca (84%) (Table S1). Some very similar species are combined into one collective species (e.g., Galium uliginosum and G. 3

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from other habitat types around the transect, several agrotolerant species of the region also are initially classified as F-species (e.g., Aegopodium podagraria, Ranunculus repens, Stellaria media, Urtica dioica; Aavik et al., 2008; Aavik and Liira, 2010). Agrotolerant species are defined as being able to inhabit an open agricultural landscape matrix. Therefore, as a correction to the earlier method (Liira and Paal, 2013), we reclassify these F-species as G-species, considering their unclear dispersal direction. As a result of the multistep classification procedure, the analysis results in 49 F-species, 38 G-species and 37 C-species (Table S1). 2.4. Trait selection To ensure objectivity in the interpretation, we address an extensive list of traits by cross-confirming filtering indicators across functionally overlapping traits. The functional classifications of traits vary (Violle et al., 2007). Therefore, we apply a robust problem-based trait system. We select traits to indicate either the dispersal filters or the establishment filters. Based on the available information on plant traits from online databases and the filtering indicator value in the literature (Whigham, 2004; detailed listing in Table S2), we consider 27 plant traits in total. Dispersal filters are indicated by the proportion of anemochory, myrmecochory, endozoochory, epizoochory and ballochory; the proportion of species dispersing with dispersules; the average dispersule and seed mass; the seed bank longevity index; the proportion of clonally reproducing species; the clonal speed rank; the proportion of abiotically and biotically pollinated species; and the flowering onset and duration. Establishment filters are indicated by plant height; the growth form (e.g., rosette, hemirosette or erosulate); the specific leaf area (SLA); and the proportion of species with mycorrhizal association. We also include some ecological complex-traits, which are widely used and appreciated for their high indicative value in ecological research (McCollin et al., 2000; Staley et al., 2013): the ecological indicator values of light, soil moisture and soil productivity (Ellenberg et al., 1991) and the CSR-strategy system (Grime et al., 1988). These are considered as establishment indicator traits because they are largely defined via establishment success or light foraging and growth properties (Ellenberg et al., 1991; Hodgson et al., 1999).

Fig. 1. Flow diagram of species classification into response groups. n.s. = nonsignificant.

palustris, Poa trivialis and P. palustris) with the assumption that their traits are usually similar. The nomenclature follows Leht (2010). We define three ecological response groups (i.e., emerging groups, Lavorel et al., 1997) according to their performance along the forestcorridor gradient. The group of study interest, forest-restricted species (henceforth, F-species), is comprised of the forest-dwelling species with a realized migration-lag into shaded corridors (Liira and Paal, 2013). Two empirical response groups are defined to quantify the optimal base values for the addressed traits in regional corridors, i.e. trait reference levels for corridors. The primary reference group is comprised of forestdwelling generalist species (henceforth, G-species), which are common in both the forest and the corridor, though the dispersal sources and sinks are unclear. The outer reference group, labelled as common corridor-dwellers (henceforth, C-species), is comprised of species common only in corridors and rare in forests; many of them are habitat generalist common also in grasslands. The F-, G- and C-species are hierarchically discriminated (Fig. 1) using the empirical spatial frequency distribution of each species along the forest-corridor transect (Corbit et al., 1999; modified method of Liira and Paal (2013)). In the first step, we discriminate between the common forest-dwelling species (i.e., F- and G-species combined) and the common species in corridors (C-species) by applying a 10% frequency threshold within a habitat type (i.e., forest or corridor). In the second step, we discriminate between F- and G-species using the shape of the frequency pattern from forest to corridor (Fig. 1). Specifically, a species is defined as an F-species when it demonstrates a declining frequency profile along the transect. All other common forest-dwelling species are defined as G-species as their frequency profiles have either a non-significant trend or an increasing trend towards the corridor. For details, see Fig. S2 with extended explanation or Liira and Paal (2013). However, since the classification of the species uses only forest and corridor data, without incorporating species occurrence information

2.5. Trait distribution signature metrics The ecological trait filtering within the F-species along the transect is evaluated using two standardized change metrics in combination: a metric to estimate the systematic change in the inter-species variability of the trait, and a metric to estimate the systematic relative shift in the mean trait value. Both metrics estimate the linear or nonlinear monotonic change of a trait distribution property (i.e., trait variability or trait mean) along the transect. These metrics are developed based on Spearman’s rank correlation (Spearman, 1904), as the use of standard statistics provides a robust statistical support for the indicator and an easy-to-interpret scale, from −1 to 1. For the shift in the trait mean, additional pre- and post-adjustments into the calculation are made (details below). We use only data from the transect distance-steps where at least two F-species are recorded, as variability estimate cannot be extracted from single species observation. For each transect, we quantified the systematic trait variability change (the VC-index) as the Spearman’s rank correlation (rS) between the trait variability (CV(trait)) of the F-species registered at each specific distance step and the distance of the plot along the transect (dist). We estimated the variability as the coefficient of variation (CV(trait)) to reduce the effect of the trait mean value driven heteroscedasticity.

VC = rS (CV (trait ); dist ) The variability in the trait is expected to decrease from the forest and along the corridor when the trait is subjected to the ecological 4

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filtration in the form of removal of unfit trait extremes. However, an increase of trait variability is also possible if the central trait values are filtered out. We estimated the systematic change in a trait mean value in Fspecies along each individual transect using an original convergence/ divergence index (the CD-index), which provides a standardized change estimate of a trait mean relative to the potential optimal level. We do not recommend the estimation of the trait mean change using only data from the group of interest (e.g., F-species) because that would require later qualitative, and sometimes subjective, comparisons with other species groups in the interpretation; e.g. this is inevitable step in an ANOVA-type approach. The commonly used ANOVA-type approach to estimate trait filtering we will use to evaluate the objectivity of the CDindex. The formula of the trait CD-index (CDRef) estimated for each transect is as follows:

Consequently, the negative values of the CD-index from zero down to −1 indicate the convergence of the trait mean of the F-species with the specific level of the trait in the reference group. The positive values of the CD-index from zero to 1 indicate the trait divergence of the F-species from the reference group. As we have two reference groups selected, then two change metrics of the trait mean, two CD-indices per trait, are produced, either relative to the G-species (CDG) or C-species (CDC). For the metric calculation, we use the function cor.test of the stats package in R. The R-script is provided in the Supplements. For the final comparative analysis, we calculated the overall mean of the VC-index or the CD-index across all transects. To consider these metrics estimates to be significantly different from zero and to show a filtering signal, we obtained the statistical critical value from t-test tables used for Spearman correlation, considering the level α = 0.05 and the number of transects as the count of independent observations (transects) for the criterion N. We evaluate the information consistency vs complementarity between both distribution signature metrics by estimating the Spearman’s correlations between them. To evaluate the results of the CD-index in traditional terms as the qualitative change pattern of trait means, we use one-way repeated measures ANOVA (function lmer in package lme4; Bates et al., 2015) with Fisher’s LSD test for post hoc pairwise comparisons (function glht in multcomp package; Hothorn et al., 2008). The transect ID is used as a random factor to define an error term for the F-statistic.

CDRef = sgn(|Δtrait(dist¯ ≥ 50m,Ref ) | − |Δtrait(dist¯ = 0m,Ref ) |) × |rS (Δtrait(dist , Ref ) ; dist )|, where Δtrait(dist , Ref ) = trait(F , dist ) − trait(Ref ) . The CD-index relative to a specific reference group (Ref ∊ {G-species, C-species}) is calculated using two components: the absolute value of Spearman’s rank correlation metric (rS) and the sign-function (sgn). The absolute value of Spearman’s rank correlation metric (rS) is estimated between the distance along the transect (dist ∊ {5, 10, 15, 25, 50, 100 m}) and the trait contrast (Δtrait(dist,Ref)). Trait contrast is a difference between the trait value in F-species at each particular distance step (trait(F,dist)) from the grand reference level, defined by the reference group of species (trait(Ref)) (Fig. 2). At some level, absolute correlation estimate could be sufficient for the interpretation, however, trait convergence and divergence might differ in reaction scale. Therefore, sign of the trait value change should be added to distinguish two contrasting responses to filtering. The original sign provided the correlation analysis is not suitable, as it would provide a biased indication of change type in these cases where the trait mean of the F-species intersects the reference level, i.e., the Δtrait changes the sign along the transect (Fig. 2, from step 5 to step 7). Therefore we included the additional sign-function into the CD-index formula. The sign of the correlation estimate is extracted from the contrast value between the average trait difference in the source habitat (at the start of the gradient; Δtrait(0m,Ref)) and the most distant step of the transect inside the target habitat (Δtrait(dist≥50m,Ref)). When there is no crossing of reference level, the CD-index formula can be reduced down to direct estimation of the Spearman’s correlation between Δtrait and distance, as is the CV-index.

3. Results 3.1. Systematic change of traits We detect a statistically significant change in distribution for 19 out of 27 traits from the forest to wooded corridors (Fig. 3). Among those, for 16 traits, we observe a decrease in variability along the transect (Fig. 3). Original VC-index estimates and p-values are reported in Table S3. For 10 traits, we detect a change in the mean value, either as a convergence with or a divergence from at least one reference group (Fig. 3). The CD-index estimates and p-values are reported in Table S3. The absolute estimate of the extreme end of convergence scale is smaller than for the divergence scale, which shows the importance of analytical distinction between them, i.e. the use of the sign function in the CD-index. The CD-index and CV-index provide different indication on the filtering intensity of traits, as there is a low correlations between the CD-index of the F- vs. the C-species and the CV-change in a trait along the distance (rS = 0.01, p = 0.97), and therefore, we can use the postulated information complementarity between indicator metrics. Only for six traits of the F-species do we observe the strongest confirmation of filtering, as the simultaneous co-occurrence of the decrease in variability and cross-confirmed convergence or divergence relative to both reference groups (Fig. 3). Four traits demonstrate a converging mean value towards both reference levels: hemirosette growth form (i.e., plants with both leaf rosette and leaved stem); higher plant stature; higher Ellenberg’s indicator value for light; and higher Rstrategy score. Note that for the R-strategy, the CD-index relative to Cspecies is negative but statistically insignificant. (lower left corner of Fig. 3). The cross-confirmed divergence of trait mean values from both reference groups occurs as a change towards greater seed mass and a higher Ellenberg’s indicator value for soil moisture (upper right corner of Fig. 3). A less clear indication of directed filtering is observed for the four traits. The change in the trait mean depends on the choice of reference group, which indicates that the reference levels differ between the Gand C-species. As the G-species group is the primary reference group, a lower proportion of species using myrmecochory and a lower proportion using ballochory are observed as trait convergence of F-species towards G-species. The greater proportion of epizoochory as well as the greater proportion of the species dispersing with dispersules are

Fig. 2. An illustration of the calculation of the trait difference at each distance step relative to the grand mean of the reference group (Δtraitdist,Ref) and the data used to estimate the CD-index per transect. Bar denotes the trait mean of the reference group. This example illustrates the trait convergence with some intersection of the F-group trait with the reference level at the step 7. 5

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observable by stepwise comparisons. However, a lack of systematic change or great variability seems to be common features of these traits (Fig. 4). Some statistically significant convergence or divergence changes (indicated by the CD-index) seem to be with secondary importance in ecological sense, as an overall greater marginal difference between the trait means in the F-species and in the reference species groups (G- and/ or C-species) dominates. For example the seed mass and Ellenberg’s indicator value for light have large gap in the mean values of species groups. Analogously, several traits with a CD-index not significantly different from zero demonstrate a consistently strong difference between the F-species and the reference groups. Specifically, the F-species differ consistently by a large margin from both reference groups in traits such as a greater S-strategy (i.e., stress-toleration) score and lower C-strategy (i.e., competitor) score, greater dispersule mass and lower proportion of anemochory (Fig. 4). Traits for which the F-species differ from only one reference group include: high clonal reproduction strategy in contrast to the G-species, and a low mycorrhizal status, clonal speed, endozoochory and epizoochory and high biotic pollination rate in contrast to the C-species (Fig. 4). 4. Discussion 4.1. Method quality We showed that the debate concerning the role of dispersal limitation and establishment limitation in corridors (McCollin et al., 2000; Whigham, 2004; Wehling and Diekmann, 2008; Paal et al., 2017) is partly due to methodological reasons, underlined here by (1) poor concurrence either between functionally redundant traits or (2) between reference groups, and also by (3) different trait patterns revealed by different analysis types. The proposed quantitative method of the CD-index effectively detects the trait response signals to transect gradient and reveals trait rankings, elucidating the nature of species ecological filtering along the forest-corridor gradient. The CD-index detects the distribution change for traits reacting on gradual intensification of filtering, as for most dispersal-related traits, and also for traits reacting instantly at the forest-corridor ecotone, as for several establishment-related traits (illustrated by ANOVA-type approach, and by Honnay et al. (2002), Wehling and Diekmann (2009b) and Brunet et al. (2012)). The CDindex also detects the filtering signal for traits which have highly distinctive mean levels between response groups along the gradient, i.e. for which the ANOVA results for filtering are inconclusive. Many of these contrasting plant traits are expert graded and define the fundamental difference between forest-restricted species and generalist species. This demonstrates the potential grade-scaling problems of these ecological indicator traits. However, the proposed standardized reaction metrics do not depend on that scale-issue. We suggest that Ellenberg ecological indicator values, Grime strategy types and clonal speed rates should be used with care when the trait mean-level forms the basis of ecological assessments (e.g., using ANOVA, or trait variability tests), since the given grades over-emphasise the habitat preference differences among species rather than reflect real niche distances.

Fig. 3. The ranking of traits based on the CD-index representing the strength of convergence/divergence between forest-restricted species and reference groups along the transect. The horizontal dashed line indicates the critical estimate of the CD-index at the level p = 0.05. Asterisks indicate a decrease in variability along the transect. The direction of the change (plus or minus sign) in the average trait value of forest-restricted species (F-species) along the transect (extracted from the ANOVA results; Table S4) is displayed only for significantly converging and diverging traits.

observed as F-species divergence from G-species (Fig. 4). The interpretation of the distribution signature of these traits relative to the Cspecies is the opposite. Nine traits partially indicate filtering, as three of these converge/ diverge without a decrease in variability, and the other six traits decrease in variability without a significant change in the trait average (Fig. 3). Convergence without a decrease in variability occurs towards a lower proportion of the rosette growth form and a longer flowering duration in corridors (Figs. 3 and 4). Divergence occurs towards shorter seed bank longevity (Figs. 3 and 4). Among the traits partially indicating filtering, those that demonstrate significant reductions in variability are: the Ellenberg’s indicator value for soil productivity, the flowering onset, the C-strategy, SLA, abiotic pollination and the dispersule mass.

3.2. Qualitative patterns of trait means The systematic change in trait means revealed by the CD-index can be recognized on the graph of trait means by distance steps presented for the F-species, where traits are grouped by CD-index (Fig. 4). A multiple comparison test results of trait means between the distance steps (Table S4) largely supports the CD-indicated monotonic change in the trait value. The trait value change is mostly incremental for dispersal traits, e.g., most evidently for the composition of dispersal vector types, the seed mass, or the use of dispersules for dispersal with some growth form types. Several establishment traits demonstrate abrupt change at the forest edge, but the CD-index successfully reflects this. Such traits are the flowering duration, the proportion of hemirosettes, the R-strategy, Ellenberg’s indicator value for light and soil moisture, and seed bank longevity (Fig. 4). In the middle graphs, where the CDindex suggests statistically non-significant changes, some patterns are

4.2. The continuum of indicators between dispersal and establishment filters Analysis results of dispersal traits indicate a filtering effect suppressing some short-distance types and favouring some long-distance dispersal types, while other dispersal traits do not react on distance or have unexpected distribution signatures. The interpretation of these few significant reactions is, however, ambiguous because of the difference in optimum trait levels suggested by the reference groups. Therefore we propose that the emphasis on dispersal limitation as a special feature of forest-specialist plants is a misconception, driven by the use of a single trait or a few indicator traits without sufficient 6

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Fig. 4. Repeated ANOVA results which compare the average trait values of the F-species’ subsets along the transect and the transect averages of G- and C-species. Letters denote homogeneity groups according to Fisher’s LSD test. Graphs are ordered according to the CD-index values presented in Fig. 3.

reference groups. We suggest that there exists a continuum of filters from dispersal to establishment limitation, where some indicator traits are filter specific, while other traits should be interpreted in complexes or seen to be simultaneously driven by various filters. Therefore, explicit role

analysis of trait distribution signature along spatial gradients and/or driven by the interpretation which is not based on quantitative comparison with other response groups or other habitat types. In contrast, establishment limitation is unequivocally indicated as an overall convergence of traits of the forest-restricted species group towards both 7

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delineation of two filter systems (dispersal vs establishment) cannot be provided. Instead, conservation management emphasis should be on the supporting species with specific traits.

term seed banks. Also, as pollinators and companions for forest plants are scarce (Graae and Sunde, 2000; Lõhmus et al., 2014) and more than 80% of observed forest-dwelling species are insect pollinated (similar to neighbouring grasslands; Lõhmus et al., 2014; Kütt et al., 2018), flowering duration should be interpreted as an establishment/persistence indicator trait. Establishment traits unequivocally pinpoint to filtering by improved light conditions and not by soil conditions (McCollin et al., 2000; Naaf and Wulf, 2011; Staley et al., 2013). Filtering by light conditions is indicated by the greater Ellenberg indicator value for light, the increase in plant height, and the reduction in the share of rosette-forming plants (i.e., without upright leafed stems) in favour of species with a hemirosette growth form (i.e., rosette species with an upright leafy stem). A leaf indicator trait, such as SLA, and a compound indicator, such as the C-strategy, both respond only with a decrease in their variability. All forest species are specialized to small-scale patch-dynamics in oldgrowth forest (Reier et al., 2005; Liira and Sepp, 2009), but forest specialists and forest generalists have different capability of benefiting from improved light conditions (Neufeld and Young, 2003; Whigham, 2004). Forest-restricted species have been shown to benefit from the stress created by tree-formed shade. Shade by trees suppresses the competitive superiority of generalist species only, but close-neighbour competition with shrubs and tree samplings suppresses forest specialists also (Adkison and Gleeson, 2004; Liira et al., 2012; Paal et al., 2017). There are no signs of filtering caused by environmental eutrophication, potentially sourced from surrounding agricultural lands (Honnay et al., 1999; McCollin et al., 2000; Whigham, 2004; Wehling and Diekmann, 2009b; Staley et al., 2013). Specifically, we did not detect significant changes in ecological indicator values for nutrient requirement (Small and McCarthy, 2005; Graves et al., 2006; Naaf and Wulf, 2011). Certain filtering responses occur which concern adaptations to soil moisture. These can be interpreted, combined with an increased share of opportunistic R-strategy forest-restricted plants, as the forest-restricted species’ use of ditch-related low-competition microsites (Adkison and Gleeson, 2004; Liira and Paal, 2013; but see Staley et al. (2013)).

4.3. Trait-filter interactions We observed the change in dispersal traits along the distance gradient as the expected decrease in percentage of myrmecochory and ballochory of forest-restricted species from the forest outward, and the expected success of species with adaptations for long-distance dispersal like epizoochory and the use of dispersules instead of bare seeds. Shortdistance dispersal traits converge only towards forest-dwelling generalists and also the estimate of grassland species in the region (Lõhmus et al., 2014), while both long-distance dispersal traits converge towards only corridor-dwellers. We did not observe filtering effects on endozoochory or dispersule mass, even though these traits have been prone to filtering in earlier studies (Wehling and Diekmann, 2009b; Hernández and Zaldívar, 2013; Lõhmus et al., 2014). These trait patterns combined indicate the suitability of corridor habitat quality for foxes and other medium-sized mammals (Heinken et al., 2002; Hovstad et al., 2009; Albert et al., 2015), while forest insects and frugivorous birds and mammals are not specifically affiliated with corridors. The greatest confusion is generated by certain indicator traits of dispersal, which may have dual ecological interpretations regarding dispersal and establishment filtering. They should be used only alongside with other functionally redundant traits to support the interpretation. For example, seed mass is a particularly widely used functional trait for indicating dispersal ability (e.g., in LHS-system of Westoby (1998), Weiher et al. (1999), Verheyen et al. (2003)), even though small-sized propagules can also have a limited dispersal range (Penrod and McCormick, 1996; Rose and Dassler, 2017) and large seeded myrmecochorous or zoochorous species can disperse to long distances (Appendix 1 in Bullock and Clarke, 2000; Lõhmus et al., 2014). Alternatively, seed size can be used as an indicator of seedling establishment support (Brunet et al., 2012; Lõhmus et al., 2014). The greater seed size in corridors indicates the importance of establishment filters over dispersal filters, as forest-restricted species with lightweight seeds generally are filtered out in corridors because of intense competition by other species (Weiher et al., 1999; Adkison and Gleeson, 2004; Moles and Westoby, 2004; Stampfli and Zeiter, 2008). As dispersal types are defined by propagule properties and the size of a single seed sometimes forms only a minor part of the dispersule, we showed that specific dispersule properties provide more univocal indication about limiting dispersal filters, while seed size should be considered the trait with dual indication properties for dispersal and establishment filtering. Clonal mobility can also be considered as a short-distance dispersal type for landscape-scale processes, as physical connectivity between habitats is required. Even though the used transect design provided spatial connectivity between forest and corridor, distance-based filtering was not observed. Interestingly, values of clonal traits were similar either to one or another of the reference groups. Apparently, the indicator role of clonal traits should be considered as scale-dependent – in landscape-scale studies they are indicators of establishment filters as the clonality backs the long-term persistence of species, while in habitat-scale studies clonal traits are indicators of dispersal filters describing the local expansion in continuous space. Analogous establishment/persistence indication is observed for flowering duration, which is expected to characterize seed rain intensity via generative reproduction effort (Neufeld and Young, 2003; Verheyen et al., 2003; Schmuki and De Blois, 2009; Wehling and Diekmann, 2009a; Naaf and Wulf, 2011). For forest-specialist plants, however, the long-term flowering is an important adaptation guaranteeing the species persistence within the habitat via continuous seed production, as forest-specialists in general have short-term seed banks (Bossuyt and Hermy, 2001; Plue et al., 2017). The forest-restricted species established in corridors are characterized by particularly short-

5. Conclusions We propose a backbone methodology which is demonstrated to be useful in ranking indicator traits and identifying limiting ecological filters in landscape setting. We conclude that the ecological filtering process can be objectively assessed and interpreted only when sampling design allows the assessment of ecologically similarly responding species and all relevant filters, and when several partly overlapping analytical approaches are used simultaneously. Analytical redundancy should be encouraged as cross-evaluation of filters, using (i) multiple traits with partly overlapping functionality; (i) two or more contrasting reference groups of species; and (iii) various analysis types. In the presented example application, we demonstrate that ecological filtering between forest and wooded corridor acts on both the dispersal and the establishment properties of forest-restricted species. However, dispersal limitation is highly nuanced, and the optimal trait level is not unequivocally clear. Many forest specialist species can even have an alternative optimal trait level in comparison to generalist species. Establishment filtering acts more uniformly and traits converge among various species groups. The high overall variability between ecological response groups, as well as the loss of variability in many traits among forest-restricted species, indicate that there cannot be a single optimal set of habitat conditions in corridors. The design of ecologically effective green corridor infrastructure with biodiversity support in mind, should emphasise the diversity of micro-environmental conditions that maximizes the habitat suitability for a wide range of species. The structure of corridors should also be attractive to plant dispersing animals, particularly to medium size mammals and forest birds. Hedgerows, tree-lines and 8

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alleys should be wide enough that trees could form an interior zone with intensive shade-stress for generalist species. The suitability of a wooded corridor for forest plants is most easily indicated by the rosetterich, low-cover and short-statute herb layer, which also supports a mixture of small-seeded species and large-seeded myrmecochorous and zoochorous species.

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Acknowledgements This project was supported by the Estonian Science Agency project IUT 20-31, the ERA-Net BiodivERsA project smallFOREST, and the European Union through the European Regional Development Fund (the EcolChange Centre of Excellence) and Horizon 2020 project EFFECT. We are grateful to prof. Guntis Brūmelis and Susanna Vain for valuable comments on the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecolind.2019.105688. References Aavik, T., Augenstein, I., Bailey, D., Herzog, F., Zobel, M., Liira, J., 2008. What is the role of local landscape structure in the vegetation composition of field boundaries? Appl. Veg. Sci. 11, 375–386. https://doi.org/10.3170/2008-7-18486. Aavik, T., Liira, J., 2010. Quantifying the effect of organic farming, field boundary type and landscape structure on the vegetation of field boundaries. Agric. Ecosyst. Environ. 135, 178–186. https://doi.org/10.1016/j.agee.2009.09.005. Adkison, G.P., Gleeson, S.K., 2004. Forest understory vegetation along a productivity gradient. J. Torrey Bot. Soc. 131, 32–44. http://www.jstor.org/stable/4126926. Albert, A., Mårell, A., Picard, M., Baltzinger, C., 2015. Using basic plant traits to predict ungulate seed dispersal potential. Ecography 38, 440–449. https://doi.org/10.1111/ ecog.00709. Aunap, R., 2011. Eesti Atlas, fourth ed. Avita, Tallinn. Bates, D., Maechler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01. Baudry, J., Bunce, R.G., Burel, F., 2000. Hedgerows: an international perspective on their origin, function and management. J. Environ. Manage. 60, 7–22. https://doi.org/10. 1006/jema.2000.0358. Beier, P., Noss, R.F., 1998. Do habitat corridors provide connectivity? Conserv. Biol. 12, 1241–1252. https://doi.org/10.1111/j.1523-1739.1998.98036.x. Bossuyt, B., Hermy, M., 2001. Influence of land use history on seed banks in European temperate forest ecosystems: a review. Ecography 24, 225–238. https://doi.org/10. 1034/j.1600-0587.2001.240213.x. Brunet, J., 2007. Plant colonization in heterogeneous landscapes: an 80-year perspective on restoration of broadleaved forest vegetation. J. Appl. Ecol. 44, 563–572. https:// doi.org/10.1111/j.1365-2664.2007.01297.x. Brunet, J., De Frenne, P., Holmström, E., Mayr, M.L., 2012. Life-history traits explain rapid colonization of young post-agricultural forests by understory herbs. For. Ecol. Manage. 278, 55–62. https://doi.org/10.1016/j.foreco.2012.05.002. Bullock, J.M., Clarke, R.T., 2000. Long distance seed dispersal by wind: measuring and modelling the tail of the curve. Oecologia 124, 506–521. https://doi.org/10.1007/ PL00008876. Corbit, M., Marks, P.L., Gardescu, S., 1999. Hedgerows as habitat corridors for forest herbs in central New York, USA. J. Ecol. 87, 220–232. https://doi.org/10.1046/j. 1365-2745.1999.00339.x. Cornell, H.V., Harrison, S.P., 2014. What are species pools and when are they important? Annu. Rev. Ecol. Evol. Syst. 45, 45–67. https://doi.org/10.1146/annurev-ecolsys120213-091759. Davies, Z.G., Pullin, A.S., 2007. Are hedgerows effective corridors between fragments of woodland habitat? An evidence-based approach. Landsc. Ecol. 22, 333–351. https:// doi.org/10.1007/s10980-006-9064-4. De Keersmaeker, L., Vandekerkhove, K., Verstraeten, A., Baeten, L., Verschelde, P., Thomaes, A., Hermy, M., Verheyen, K., 2011. Clear-felling effects on colonization rates of shade-tolerant forest herbs into a post-agricultural forest adjacent to ancient forest. Appl. Veg. Sci. 14, 75–83. https://doi.org/10.1111/j.1654-109X.2010. 01101.x. De Sanctis, M., Alfò, M., Attorre, F., Francesconi, F., Bruno, F., 2010. Effects of habitat configuration and quality on species richness and distribution in fragmented forest patches near Rome. J. Veg. Sci. 21, 55–65. Deckers, B., Verheyen, K., Hermy, M., Muys, B., 2004. Differential environmental response of plant functional types in hedgerow habitats. Basic Appl. Ecol. 5, 551–566. https://doi.org/10.1016/j.baae.2004.06.005. van Dorp, D., Opdam, P.F.M., 1987. Effects of patch size, isolation and regional abundance on forest bird communities. Landsc. Ecol. 1, 59–73. https://doi.org/10.1007/ BF02275266. Dupré, C., Ehrlén, J., 2002. Habitat configuration, species traits and plant distributions. J. Ecol. 90, 796–805. https://doi.org/10.1046/j.1365-2745.2002.00717.x.

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