Analyzing biological traits of riparian forest along ecoregions and local habitats to define functional targets for their restoration at different scales

Analyzing biological traits of riparian forest along ecoregions and local habitats to define functional targets for their restoration at different scales | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analyzing biological traits of riparian forest along ecoregions and local habitats to define functional targets for their restoration at different scales Edgardo Javier Ignacio Pero, Mayra Alejandra Piccinetti, María Celina Reynaga This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7775825/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Riparian forests perform a variety of functions but are among the most threatened environments. The objective of this study was to define functional targets for the restoration of riparian forest through an analysis of biological traits and its relationship with local geomorphological variables in Yungas subtropical forest and Dry Chaco Forest from northwestern Argentina. The composition and abundance of woody and herbaceous species were sampled. Twelve functional traits were characterized for 91 species based on field data and literature, which were ordered using fuzzy coding. According to RLQ analysis, three types of trait associations were identified: 1) Taller plants, large leaf size, elliptical form, evergreen phenology, flowering and fructification period in winter, associated to adjacent areas of greater slope and altitude, located in the Yungas forest; 2) Shorter plants, lanceolate leaf form, dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, low woody density, associated to greater channel width and flooding area and lower slopes, corresponding to the Dry Chaco; and 3) An intermediate group of sites that are located at the foothills and transition zone between ecoregions, with a variety of trait modalities, mainly medium leaf size, fleshy fruit type, and zoochory dispersal syndrome. Although a group of common functional traits may not be identified in the riparian zones, it was possible to associate some functional characteristics to the dimensions of riparian areas, helping to guide forest restoration targets along different landscape units, both in their species composition and in their functional structure. functional ecology Yungas subtropical forest Dry Chaco dispersal syndromes fluvial landscape ecosystem restoration Figures Figure 1 Figure 2 Introduction Riparian forests are considered an interface between terrestrial and aquatic ecosystems and are among the most vulnerable environments to both climate change and human impact (Capon et al. 2013 ). The importance of this land–water interface has been emphasized for many reasons: they are extremely dynamic environments in terms of structure, function, and diversity, and they reinforce abiotic–biotic feedbacks (Naiman et al. 1993 ; Pokrovsky 2016 ; Pinay et al. 2018 ). According to Naiman et al. ( 2005 ), riparian forest is defined as the vegetation directly adjacent to rivers and streams. This forest extends laterally from the active channel to the uplands, including active floodplains and the immediately adjacent terraces. Many authors have identified characteristic vegetation within riparian zones, with different compositions, structures, and functions from that of the adjacent vegetation (Gregory et al. 1991 ; Naiman et al. 1993 ; Tang and Montgomery 1995 ; Prach and Straskrabová 1996 ; Naiman and Décamps 1997 ). However, few studies over the last decades have quantified changes in riparian and adjacent forest relations across landscape units or ecoregions that have marked climatic or geographic differences (Pinnay et al. 1990; Naiman et al. 1992 ; Cattaneo et al. 1995 ). In recent years, there has been a renewed interest in studying the relation between riparian vegetation and hydrogeomorphological processes from new conceptual frameworks (e.g., Steiger et al. 2005 ; Corenblit et al. 2007 ; 2015 ), even though few studies have addressed this issue from a landscape perspective (Kim and Kupfer 2016 ; Kujanova et al. 2018). Although riparian vegetation may vary in its structure and composition across different landscape units (Pero and Quiroga 2019 ), it could be expected that the riparian communities share a set of functional traits among ecoregions regardless of their species identities. Functional traits of biological communities (strategies to maximize their fitness and survival in the face of different spatial and temporal characteristics of the habitat (Poff 1997 )) link community structure to ecosystem processes (Diaz et al. 2007; Webb et al. 2010 ). By moving beyond species identity, trait-based approaches also enable comparisons of communities across systems (Cadotte et al. 2011 ), which allows better generalization of research results, and for example, to achieve functional targets for ecosystem restoration as a critical issue for effective mitigation of ecological degradation (Gornish et al., 2023 ; Laughlin 2014 ; Merchant et al. 2022 ). Moreover, in riparian zones, most of the previous studies using a functional approach have focused on a single environmental gradient such as, the flood gradient (Aguiar et al. 2013 ; Bejarano et al. 2017 ; McCoy-Sulentic et al. 2017 ; Gaudichet et al. 2023 ), or to the effects of interactions between it and human-mediated environmental gradients (see e.g., Brummer et al. 2016 ; Dawson et al. 2017 ; Janssen et al. 2019 ), but no study has focused on traits variations along ecoregional gradients. Some studies analyzed traits variation in riparian areas along ecotones. For example, Lamb and Mallik ( 2003 ) found that several traits, including deciduous leaves, wind and water-borne diaspore dispersal, wind pollination, rhizomatous clonal growth, nitrogen fixation, and the phalanx clonal growth form, all declined in prevalence from the streambank to the forest. Another group of traits, including vertebrate diaspore dispersal and ericoid mycorrhizae, displayed the opposite pattern, increasing in prevalence from the streambank to the forest. Kyle and Leishman ( 2009 ), examined the patterns of plant functional trait variation in relation to geomorphology on three geomorphic surfaces (point bar, bench and bank) along the Upper Hunter River, Australia. They found that generally the point bar was associated with species that were herbaceous, with small seed mass, a short stature and a high specific leaf area (SLA). Conversely, the bench was associated with grasses that had unassisted seed dispersal and intermediate seed mass and SLA, while species on the bank had tall stature, large seed mass, a high SLA and a perennial life cycle. In subtropical rainforest and dry forest of Argentina, Pero and Quiroga ( 2019 ) revealed that the riparian forest may be very different from the adjacent, mainly in species dominance. However, the hypothesis that differences between riparian and adjacent zones would be less marked in humid than semiarid regions was not supported by their results. Marked differences in geomorphological and physical streamside features were found between the ecoregions studied by Pero and Quiroga ( 2019 ), and they were strongly associated to assemblage distribution. It could be expected that riparian communities from contrasted ecoregions such as the Yungas rainforest and Western Chaco dry forest share a set of functional traits among ecoregions regardless of their species identities. Furthermore, to incorporate functional targets in restoration processes, the functional structure of the reference model must be well known (Gann et al. 2019 ). The region has a high deficit of riparian forest due to the changes in land uses that have occurred in recent decades (Pero et al. 2020a). A reference model was defined for rivers (Pero et al. 2020b) and riparian zones (Pero and Quiroga 2019 ) of northwestern Argentina, but functional traits have not been included. Accordingly, the main objective of the present study was to analyze the functional structure (based on biological traits) of the riparian forest within local habitat and between the humid and semiarid ecoregions mentioned. Firstly, we analyzed the physical variables and the physiography of the streamside to compare the geomorphology among sites. Secondly, we compared the composition and structure of tree, bush, and liana species between the forest zones located next to the river and those located farther away. Thirdly, we compared functional dissimilarities in forest sectors between ecoregions to analyze variations across landscapes. Finally, we proposed a functional reference model for the regional restoration of riparian forest. Materials and methods Study area The study area is located between 26–28S and 66–64W, including most of Tucumán province and their borders with Santiago del Estero province in Northwestern Argentina (Fig. 1 ). The area covers a wide zone with heterogeneous landscapes containing diverse ecosystems such as deserts, mountain cloud forests, dry forests, and grasslands (Brown and Pacheco 2006 ). In this study, we sampled streams located in two different ecoregions: The Yungas subtropical cloud forest and the Western Chaco dry forest. The Yungas subtropical cloud forest (Yungas forest) is a narrow belt of mountain rainforest that ranges from 400 to 3000 m a.s.l. (Brown 2000 ). The Yungas forest is part of a long chain of mountain cloud forests that extends along the east side of the Andes Mountains of South America from Venezuela to northwestern Argentina. The climate is warm and humid, with mean annual temperatures ranging from 14 to 26°C and rainfall from 1000 to 2500 mm (Hueck 1978 ). The Yungas forest is stratified into three vegetation floors or bands. The high montane forest (1500–3000 m a.s.l.) contains monospecific tree stands that are usually either Alnus acuminata or Podocarpus parlatorei . Rainfall reaches 1000 mm. The main human activity in this area is scattered cattle and fire to maintain pastures (Brown and Pacheco, 2006 ). The low montane forest (700–1500 m a.s.l.) has the most diverse vegetation, with many evergreen species, and is dominated by Cinnamomum porphyrium and Blepharocalyx salicifolius . The low montane forest also has the highest precipitation (2000 mm annually) and the least seasonal hydrological regime. The foothill forest (400–700 m a.s.l.) contains deciduous trees and is dominated by Tipuana tipu and Enterolobium contortisiliquum . The annual rainfall on this floor varies between 1000–1500 mm during the wet season, and the 6-month dry season (50 mm rainfall) extends from June to November (Brown et al., 2001 ). This area is the one, most widely modified by human activities at present, with the main urban centers and industrial activities (sugar and citrus) located in it (Brown and Pacheco, 2006 ). The Western Chaco ecoregion is a vast sedimentary fluvial plain formed by the streams or rivers that run northwest to southeast and includes parts of northwestern Argentina, southeastern Bolivia, northwestern Paraguay, and southwestern Brazil (Great South American Chaco). The headwaters are located in the mountains, outside the region to the west, and they transport great quantities of sediments into the region. Mean annual temperatures range between 19 and 24°C. Mean annual rainfall varies between 400 and 900 mm, with most precipitation falling in the summer and little falling in the winter (Minneti 1999 ). The vegetation is composed of dry forests and segregated grasslands. This ecoregion is classified into three sub-ecoregions: Arid Chaco, Semiarid Chaco, and Chaco Serrano (Brown and Pacheco 2006 ). Only the latter two are represented in the study area. The Chaco Serrano is part of the western border of the ecoregion and is characterized by low mountain topography. It is bordered in some places by the Yungas forest. The Semiarid Chaco occupies the greater portion of the ecoregion and is a continuous xerophytic and semi-deciduous forest. A wide transition zone occurs between the Western Chaco and the Yungas forest, which includes species common in both ecoregions (Cabrera 1976 ), although it is currently highly modified by agricultural use (Gasparri 2016 ). Sampling design and methods Ten sites were surveyed, each consisting of a stream or river reach of around 100 m in length (Fig. 1 ). Four sites were located in the Yungas forest ecoregion (Apeadero Muñoz [High montane forest], Las Conchas [Low montane forest], and El Sonador streams and Pueblo Viejo river [Foothill forest]) and the other six in the Western Chaco ecoregion (Tala and Salí [Chaco Serrano] and Chico, Marapa, and two sites in Urueña river [Semiarid Chaco]) (geographic coordinates in Online Resource 1). All the sites selected were minimally impacted by human activities and were designed as reference sites for ecoregions (Pero et al. 2019; Pero and Quiroga, 2019 ) and river types (Pero et al. 2020). Nevertheless, the sites located in Western Chaco were closer to human settlements and had some sign of cattle presence in the area, such as dung. A block design was performed to minimize the differences among sites in the analyzes (Feinsinger 2001 ). Three longitudinal transects randomly distributed (left or right riparian margin) and situated in a perpendicular direction from the stream or river channel were surveyed in each sampling site (Fig. 1 ). Each transect was divided into sampling units (SU) of 5 m in length and 1 m in width, totaling 10 SU per transect. The first four SU (0 to 20 m) were considered a priori as the ‘‘riparian forest’’ sectors closest to the water course and the last four (30 to 50 m) were considered the ‘‘adjacent forest’’ sectors distant from the water course. The middle SU (20 to 30 m) were considered a buffer area between forest sectors and were therefore not included in the analyzes (Feinsinger 2001 ). The composition and structure of riparian and adjacent forests were surveyed through transects, totaling 120 m 2 surveyed in each site (60 m 2 per forest sector). In each transect, the identity, basal area (calculated using diameter at breast height, DBH) and height of each tree, bush, liana, and fern individual were registered. Only specimens with more than 50 cm in height and 1 cm in DBH were considered. Specimens were identified to species level following the South American catalog for vascular plants (Zuloaga et al. 1994 ; Zuloaga and Morrone 1996; Zuloaga and Morrone 1999). All species found were listed in a table (Online Resource 2). In addition, at each transect, the lateral slope of the river margins was measured using a clinometer, which was aligned between two distant objects (1-m-high sticks) every 10 m to produce a physiographic lateral view of the margins. A longitudinal slope was obtained from a digital elevation map (ASTER DEM 30x30 m resolution) and calculated using Geographic Information Systems (GIS) software (QGIS 2014). The widths of the wet channel and floodplain (the area between the wet channel banks and the base of the enclosing valley walls, Naiman et al. 2005 ) were measured with a metric ruler in each site. Site C6 was not completed and only two transects were surveyed in it due to climatic conditions during the sampling work. Site Y4 had a canyon-constrained reach and it was therefore very difficult to survey the adjacent forest sectors completely. Sampling was carried out during October 2015 and May 2016. Functional traits definition The definition of the biological traits of the organisms consists of identifying the characteristics that carry some ecological significance (Tachet et al. 2002 ). It includes the different modalities or forms that a trait can take, established mainly by its ability to use environmental resources, overcome environmental stress, etc. For this study, ten biological traits were defined, with their respective modalities (Table 1 ). Traits were assigned to each species using various sources, including: (1) regional floras (Digilio and Legname 1966 ); (2) botanical monographs; (3) different databases: the BIOLFLOR trait base ( http://www2.ufz.de/biolflor/ index.jsp); TRY database (Kattge et al. 2019 , public data only); Kew Database. Royal Botanic Gardens Kew 2016, http://data.kew.org/sid/ ; eHALOPH https://www.sussex.ac.uk/affiliates/halophytes/;LEDA https://uol.de/en/landeco/research/leda;FLOWBASEhttps://www.isa.ulisboa.pt/proj/flowbase/ ; and (4) field observations. Some traits such as height and life form were obtained by direct observation of specimens at the field. The table of biological traits was built using fuzzy coding, which denotes the degrees of affinity exhibited by each taxon towards each feature modality (Online Resource 3). Value 0 is assigned in case of zero affinity of the taxon for a given modality, as opposed to the value 1, which indicates unequivocal affinity towards the modality in question (Chevenet et al. 1994 ). Table 1 Functional traits and their modalities. Functional trait Modality Height (m) C1 (0,5–2) C2 (2–5) C3 (5–10) C4 (10–20) Leaf type Simple Pinnate Bipinnate Trifoliate Leafless Leaf form Lanceolate Elliptical Oblong Ovate Linear Other Leaf size (cm) Small ( 10) Life form Tree Shrub Liana Herbaceous Fruit type Dry Fleshy Fruit size (cm) Very small ( 6) Dispersion type Autochory Hydrochory Anemochoral Zoochory Fenology Evergreen Deciduous Flowering period Summer Autumn Winter Spring Fructification period Summer Autumn Winter Spring Wood density (g/cm 3 ) Low (0–0,4) Medium (0,4 − 0,7) High (> 0,7) No wood Data Analysis The study of the relationships between vegetation and its environment involves the analysis of two tables: a taxonomic table, which expresses the taxon abundances in sampling units, and the environmental table that records quantitative values or categorical of environmental characteristics associated to the same units. A third table arranges data on traits distributed among the different taxa. Guided by the concept of Habitat Templet, it is intended to relate to the features biological with the environmental conditions where/are frequent; that is, it is necessary to cross the information contained in the preceding tables: 1) sampling units x environmental variables (environmental table R), 2) taxa x units of sampling (taxonomic table L), and 3) taxa x biological traits (biological traits table Q). The statistical technique that allows the ordering of the three tables of interest is the RLQ analysis (R mode; Q-mode; and L-link between R and Q), described by Doledec et al. (1996). The variables contained in R and Q can be qualitative and/or quantitative. The sampling units (SU) have been made to correspond to space-time units study (i.e., a particular site surveyed in a defined date), thus obtaining a total of 20 SUs. A correspondence analysis was performed (CA) on the taxonomic table L with its values of abundance previously log-transformed (x + 1) to access a simultaneous sort of SUs and supporting taxa. The effect of the transformation was to smooth out the differences in abundance between dominant and rare taxa. The analysis of the environmental table R was carried out with a Hill-Smith (AHS) analysis (Hill and Smith 1976 ), which is suitable for mixed situations in which they combine qualitative and quantitative variables. Finally, a correspondence analysis was used (ACF) (Chevenet et al. 1994 ) to explore the table of traits Q. For the purposes of investigating the joint structure of the three legal systems previously performed (AC, AHS and ACF) are applied the RLQ analysis, which allowed deducing the relationship between biological traits and environmental variables. The significance of the co-structure pattern between tables was examined using a non-parametric test based on 1000 random permutations of the rows, both of R as of Q. Analyzes and graphs were performed with the ade4 package (Thioulouse et al. 1997 ; Dray and Dufour 2007) of the R environment (version 2.7.2) for mathematics and statistics (Ihaka and Gentleman 1996 ; R Development Core Team 2008). Results A total of 91 plant species were identified in the study sites (Online Resource 2). The first two axes of the RLQ analysis represented 91.2% and 4.5%, respectively, of the total inertia of the cross table of environmental characteristics and biological traits (Table 2 ). The permutation test was significant for 1000 random realizations (P = 0.009). The variances were compared obtained by the RLQ analysis with respect to the individual analyzes to obtain the percentage of representation of them in the global analysis: 1) the first axis of the RLQ decomposition captures 99.8% of the variability of environmental characteristics in the separate Hill-Smith analysis (R/RLQ), 2) a correlation was found between the flora table and the first RLQ axis. This value can be compared with the maximum value correlation between sites and taxa given by the square root of the first eigenvalue of AC (𝜆=0.781). Thus, the first RLQ axis explains 61.8% of the variability contained in the floral table L (L/RLQ). 3) Variability found for biological traits by the first axis of RLQ, in relation to the obtained by the individual ACF analysis, is 75.5% (Q/RLQ). Figure 2 summarizes the results obtained from the RLQ analysis. Wet channel width and floodplain width were the environmental variables associated negatively to the first axis of analysis, while longitudinal and lateral slopes do in a positive way. Table 2 RLQ analysis summary. Eig = eigenvalues. RLQ analysis Eig 1 Eig 2 Variance 0,28 0,01 Variance percentage (%) 91,22 4,48 R/RLQ Eig 1 Eig 1 + 2 Variance 2,82 3,38 Variance percentage (%) (%) 99,8 96,6 L/RLQ Eig 1 Eig 2 Variance 0,61 0,38 Variance percentage (%) (%) 61,8 39,1 Q/RLQ Eig 1 Eig 1 + 2 Variance 0,26 0,44 Variance percentage (%) 75,5 66,2 The combined analysis between environmental variables, biological traits and taxa allows us to distinguish three main groups. By one side (negative axis 1), present sites that have higher longitudinal and lateral slopes, all of them from Yungas ecoregion. Trait modalities associated to that group of sites were height between 10 and 20 meters, large leaf size and elliptical form, evergreen leaf phenology, flowering and fructification period in winter ( Psycotria carthagenensis , Ocotea porphyria , Juglans australis ). On the other side (positive axis 1), present sites that have higher wet channel and floodplain width, mainly from Dry Chaco ecoregion. Trait modalities associated to that group of sites were height between 2 and 5 meters, lanceolate leaf form, the dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, low woody density ( Salix humboldtiana, Tessaria integrifolia, T. dodoneifolia, Erythrina crista-galli, Sapium haematospermun, Tamarix rammosissima ). An intermediate group can be distinguished at the intersection of the axes and present the sites that are located at the foothills and transition zone between Yungas and Chaco ecoregion. A variety of trait modalities were associated to this group, but the most prominent are medium leaf size, leafless, liana and herbaceous life form, fleshy fruit type, and zoochory dispersal syndrome. Discussion Physical variables and the geomorphology of the streamside markedly influenced the distribution of taxonomical and functional features of species among forest sectors. A set of functional traits modalities related to a set of species were associated mainly with physical variations across ecoregions. In addition, differences between local forest sectors (riparian and adjacent) were less marked than those along ecoregions. Three main groups of sites were identified from the combination of environmental, taxonomical and functional characteristics. One group of sites were characterized by boxed margins in mountain forest, another group by lowland areas with wider floodplains and channels, and an intermediate group that included foothill areas. Therefore, an ecoregional and geomorphological gradient was evidenced. We couldn´t differentiate a common set of functional traits modalities in riparian communities from the contrasted ecoregions analyzed. Hence, the hypothesis that riparian zones share functional traits among ecoregions regardless of their species identities was not supported by the obtained results. Although riparian zones did not share a set of functional traits modalities across ecoregions, some functional characteristics could be associated to the dimensions of riparian areas. For example, intermediate height, lanceolate leaf form, the dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, and low woody density were mainly related to wider floodplains and channels, where species associated to riparian zones where located (Pero and Quiroga 2019 ). Hence, that assembly of species could be considered as a specific guild for riparian zones with wider floodplain and wet channel habitats (Merritt et al. 2010 ; Stromberg and Merritt 2015 ). Coincidently, another study found that several traits, including deciduous leaves, wind and water-borne diaspore dispersal, and wind pollination, all declined in prevalence from the streambank to the forest (Lamb and Mallik 2003 ). Similarly, Kyle and Leishman ( 2009 ) revealed that herbaceous species, with a short stature and a high specific leaf area (SLA) were associated with point bars of river channels, while tall stature and perennial life cycle species were associated with streambanks. In addition, other trait modalities were associated to intermediate sites where floodplain and wet channel were narrower, such as fleshy fruit type, and zoochory dispersal syndrome, as it was observed by Lamb and Mallik ( 2003 ), where vertebrate diaspore dispersal increased in prevalence from the streambank to the forest. The knowledge acquired about the functional structure of riparian vegetation throughout the ecoregions studied is essential to better understand ecological processes in riparian areas. Some interesting relations were observed between ecological-response traits (Diehl et al. 2017 ) and geomorphological features of riparian sectors. For example, the relation between a relative intermediate height, lanceolate leaf form, and low wood density with wider floodplain and channel areas could reflect plants adaptations to water availability and fluvial disturbances (Merritt 2013 ). Similarly, Stromberg and Merrit (2015) found that leaf length and wood density were inversely related and that plants with lower wood density had affinities to wetter habitats and were less tolerant of drought stress (Diehl et al. 2017 ). In addition, knowing the structure of morphological-effect traits of riparian vegetation will allow us to better understand its influence on geomorphological processes (geomorphic functions) (Diehl et al. 2017 ). Accordingly, it would be important to analyze other type of traits that influence the flow of water, transport of sediment, and stabilization of landforms, such as root architecture and root depth, because determines the plants ability to draw alluvial water and influences stream-bank and bar stability (Pollen-Bankhead and Simon 2009 ). Furthermore, knowing better the functional characteristics of riparian ecosystems is essential for the conservation, restoration and management of these threatened environments. For instance, a response-and-effect trait framework can generate assemblages of indigenous species to achieve desired community responses and/or achieve desired effects on ecosystem functions (Laughlin 2014 ; Merchant et al. 2022 ; Gornish et al. 2023 ). In summary, although a group of common functional traits may not be identified in the vegetation of riparian zones, it is possible to associate some plants' functional characteristics with the dimensions of riparian areas. Therefore, knowing this group of functional traits and species associated with the different habitats or types of environments on the riparian zones will allow better definition of conservation and restoration goals including the heterogeneity found in these ecosystems. The results are important to better understand the ecological processes that occur in riparian areas, for example, those related to water or flood regulation, biogeomorphological processes related to erosion control, or seed dispersal and the provision of habitat and food for other organisms. Knowing better the functional structure of these communities in reference sites will allow us to improve the conservation and restoration of riparian environments to maintain and recover their functions (Gann et al. 2019 ). Declarations Author Contribution E.J.I.P. conceived the research idea; E.J.I.P. and M.P. collected data; M.C.R. performed statistical analyses; E.J.I.P., with contributions from M.P. and M.C.R., wrote the paper; all authors discussed the results and commented on the manuscript. Acknowledgement We are grateful to Sofia Malcum, Mario Feylling, Nicolas Laguna, Sebastian Albanesi, Guillermo Hankel, Dante Loto, and Carlos Navarro for their assistance in sampling trips; to Luciana Cristobal for helping to edit the image of the study area. This work was supported by Grants from the National Agency I+D, Argentina (PICT 2020-2447 and 2021-0058) and doctoral and postdoctoral scholarships from the National Council of Scientific and Technical Research (CONICET, Argentina). References Aguiar FC, Cerdeira JO, Martins MJ, Ferreira MT (2013) Riparian forests of Southwest Europe: are functional trait and species composition assemblages constrained by environment? J Veg Sci 24:628–638. https://doi.org/10.1111/jvs.12009 Bejarano MD, Nilsson C, Aguiar FC (2017) Riparian plant guilds become simpler and most likely fewer following flow regulation. J Appl Ecol 55:365–376. https://doi.org/10.1111/1365-2664.12949 Brown AD (2000) Development threats to biodiversity and opportunities for conservation in the mountain ranges of the upper Bermejo river basin, NW Argentina and SW Bolivia. Ambio 29:445–449 https://doi.org/10.1579/0044-7447-29.7.445 Brown AD, Grau HR, Malizia LR, Grau A (2001) Argentina. In: Kapelle M, Brown AD (eds) Neotropical Cloud Forests (Spanish). INBio, Heredia, Costa Rica, pp. 623–659 Brown AD, Pacheco S (2006) Proposal to update the ecoregional map of Argentina (Spanish). In: Brown A, Martínez Ortiz U, Acerbi M, Corcuera J (eds) The Argentine environmental situation 2005. Fundación Vida Silvestre, Buenos Aires, pp. 28–31 Brummer TJ, Byrom AE, Sullivan JJ, Hulme PE (2016) Alien and native plant richness and abundance respond to different environmental drivers across multiple gravel floodplain ecosystems. Divers Distrib 22:823–835 https://doi.org/10.1111/ddi.12448 Cabrera AL (ed) (1976) Argentine Phytogeographic Regions (Spanish). 2nd edn. Editorial Acme S.A.C.I., Buenos Aires Cadotte MW, Carscadden K, Mirotchnick N (2011) Beyond species: functional diversity and the maintenance of ecological processes and services. J Appl Ecol 48:1079–1087 https://doi.org/10.1111/j.1365-2664.2011.02048.x Capon SJ, Chambers LE, Mac Nally R, Naiman RJ, Davies P, Marshall N, Pittock J, Reid M, Capon T, Douglas M, Catford J, Baldwin DS, Stewardson M, Roberts J, Parsons M, Williams SE (2013) Riparian ecosystems in the 21st century: hotspots for climate change adaptation? Ecosystems 16:359–381 Cattaneo A, Salmoiraghi G, Gazzera S (1995) The rivers of Italy. In: Cushing CE, Cummins KW, Minshal GW (eds) River and stream ecosystems. Elsevier, Amsterdam, pp. 479–505 Chevenet F, Dolédec S, Chessel D (1994) A fuzzy coding approach for the analysis of long-term ecological data. Freshwat Biol 31:295–309 Corenblit D, Tabacchi E, Steiger J, Gurnell AM (2007) Reciprocal interactions and adjustments between fluvial landforms and vegetation dynamics in river corridors: a review of complementary approaches. Earth Sci Rev 84:56–86 Corenblit D, Davies NS, Steiger J, Gibling MR, Bornette G (2015) Considering river structure and stability in the light of evolution: feedbacks between riparian vegetation and hydrogeomorphology. Earth Surf Proc Land 40:189–207 Dawson SK, Warton DI, Kingsford RT, Berney P, Keith DA, Catford JA (2017) Plant traits of propagule banks and standing vegetation reveal flooding alleviates impacts of agriculture on wetland restoration. J Appl Ecol 54:1907–1918. https://doi.org/10.1111/1365-2664.12922 Díaz S, Lavorel S, de Bello F, Quétier F, Grigulis K, Robson TM (2007) Incorporating plant functional diversity effects in ecosystem services assessment. Proc Natl Acad Sci USA 104:20684–20689 https://doi.org/10.1073/pnas.0704716104 Diehl RM, Merritt DM, Wilcox AC, Scott ML (2017) Applying functional traits to ecogeomorphic processes in riparian ecosystems. BioScience 67:729–743 https://doi.org/10.1093/biosci/bix080 Digilio APL, Legname EP (1966) The indigenous trees of the province of Tucumán (Spanish). Opera Lilloana 15:1–278 Dolédec S, Chessel D, Ter Braak CFJ, Champely S (1996) Matching species traits to environmental variables: a new three-table ordination method. Environ Ecol Stat 3:143–166 Dray S, Dufour AB, Thioulouse J (2017) Package ade.4. Analysis of ecological data: Exploratory and Euclidean methods in environmental sciences. R-Project 20:31:18 UTC. https://pbil.univ-lyon1.fr/ADE-4 Feinsinger P (2001) Designing field studies for biodiversity conservation. Island Press, Washington DC Gann GD, McDonald T, Walder B, Aronson J, Nelson CR, Jonson J, Hallett JG, Eisenberg C, Guariguata MR, Junguo L, Hua F, Echeverría C, Gonzales E, Shaw N, Decleer K, Dixon KW (2019) International principles and standards for the practice of ecological restoration. 2nd edn. Restor Ecol 27:1–46 Gasparri NI (2016) The transformation of land-use competition in the Argentinean Dry Chaco between 1975 and 2015. In: Niewöhner J, Bruns A, Hostert P, Krueger T, Nielsen JØ, Haberl H, Lauk C, Lutz J, Müller D (eds) Land use competition: ecological, economics and social perspectives. Springer, Berlin, pp. 59–73 Gaudichet C, Greulich S, Grelier S, Janssen P, Rodrigues S (2023) Influence of local environmental gradients on ecological strategies of herbaceous communities in riverine side channels. J Veg Sci 35:1–16. https://doi.org/10.1111/jvs.13227 Gornish ES, Campbell C, Svejcar L, Munson SM, Vaughn K, Spaeth MK, Yelenik SG, Wolf A, Mitchell R (2023) Functional traits are used in restoration practice: a response to Merchant et al. (2022). Restor Ecol 31:e13880 Gregory SV, Swanson FV, McKee WA, Cummins KW (1991) An ecosystem perspective of riparian zones. BioScience 41:540–551 Hill MO, Smith AJE (1976) Principal component analysis of taxonomic data with multi-state discrete characters. Taxon 25:249–255 Hueck K (1978) The forests of South America. Ecology, composition and economic importance (Spanish). Sociedad Alemana de Cooperación Técnica (GTZ), Berlin Ihaka R, Gentleman R (1996) A language for data analysis and graphics. J Comput Graph Stat 5:299–314 Janssen P, Piégay H, Pont B, Evette A (2019) How maintenance and restoration measures mediate the response of riparian plant functional composition to environmental gradients on channel margins: insights from a highly degraded large river. Sci Total Environ 656:1312–1335. https://doi.org/10.1016/j.scitotenv.2018.11.434 Kattge J, Bönisch G, Díaz S, Lavorel S, Prentice IC et al (2019) TRY plant trait database – enhanced coverage and open access. Glob Change Biol 26:119–188 Kim D, Kupfer JA (2016) Tri-variate relationships among vegetation, soil, and topography along gradients fluvial biogeomorphic succession. PLoS ONE 11:e0163223. https://doi.org/10.1371/journal.pone.0163223 Kujanová K, Matausková M, Hosek Z (2018) The relationship between river types and land cover in riparian zones. Limnologica 71:29–43 Kyle G, Leishman MR (2009) Plant functional trait variation in relation to riparian geomorphology: the importance of disturbance. Austral Ecol 34:793–804 Lamb EG, Mallik AU (2003) Plant species traits across a riparian-zone/forest ecotone. J Veg Sci 14:853–858 Laughlin DC (2014) Applying trait-based models to achieve functional targets for theory-driven ecological restoration. Ecol Lett 17:771–784 McCoy-Sulentic ME, Kolb TE, Merritt DM, Palmquist E, Ralston BE, Sarr DA, Shafroth PB (2017) Changes in community-level riparian plant traits over inundation gradients, Colorado River, Grand Canyon. Wetlands 37:635–646 Merchant TE, Henn JJ, de Silva I, Van Cleemput E, Suding KN (2022) Four reasons why functional traits are not being used in restoration practices. Restor Ecol 31:e13788 Merritt DM (2013) Reciprocal relations between riparian vegetation, fluvial landforms, and channel processes. In: Shroder J (ed-in-chief), Wohl E (ed) Treatise on geomorphology: fluvial geomorphology. Elsevier, San Diego, pp. 219–243. https://doi.org/10.1016/B978-0-12-374739-6.00239-6 Merritt DM, Scott ML, Poff LM, Auble GT, Lytle DA (2010) Theory, methods and tools for determining environmental flows for riparian vegetation: riparian vegetation–flow response guilds. Freshwat Biol 55:206–225 Minneti JL (1999) Climatic atlas of the Argentine Northwest (Spanish). Fundación Zon Caldenius, Tucumán Naiman RJ, Beechie TM, Benda LE, Berg DR, Bisson PA, MacDonald LH, O’Connor MD, Olson PL, Steel EA (1992) Fundamental elements of ecologically healthy watersheds in the Pacific Northwest coastal ecoregion. In: Naiman RJ (ed) Watershed management: balancing sustainability and environmental change. Springer, New York, pp. 127–188 Naiman RJ, Décamps H (1997) The ecology of interfaces: riparian zones. Annu Rev Ecol Syst 28:621–658 Naiman RJ, Décamps H, Pollock M (1993) The role of riparian corridors in maintaining regional biodiversity. Ecol Appl 3:209–212 Naiman RJ, Décamps H, McClain ME (2005) Riparia. Ecology, conservation and management of streamside communities. Elsevier Academic Press, London Pero EJI, Quiroga PA (2019) Riparian and adjacent forests differ both in the humid mountainous ecoregion and the semiarid lowland. Plant Ecol 220:481–498. https://doi.org/10.1007/s11258-019-00929-w Pinay G, Bernal S, Abbott BW, Lupon A, Martí E, Sabater F, Krause S (2018) Riparian corridors: a new conceptual framework for assessing nitrogen buffering across biomes. Front Environ Sci 6:47 Pinay G, Décamps H, Chauvet E, Fustec E (1990) Functions of ecotones in fluvial systems. In: Naiman RJ, Décamps H (eds) The ecology and management of aquatic-terrestrial ecotones. Parthenon Publishing Group, Carnforth, pp. 141–169 Poff NL (1997) Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. J N Am Benthol Soc 16:391–409 Pokrovsky OS (2016) Riparian zones: characteristics, management practices and ecological impacts. Nova Science Publishers, New York Pollen-Bankhead N, Simon A (2009) Enhanced application of root reinforcement algorithms for bank-stability modeling. Earth Surf Proc Land 34:471–480 Prach K, Straskrabová J (1996) Restoration of degraded meadows: an experimental approach. In: Prach K, Jeník J, Large ARG (eds) Floodplain ecology and management. Academic Publishing, Amsterdam, pp. 87–93 QGIS Development Team (2016) QGIS geographic information system R Core Team (2019) R: a language and environment for statistical computing Steiger J, Tabacchi E, Dufour S, Corenblit D, Peiry J-L (2005) Hydrogeomorphic processes affecting riparian habitat within alluvial channel-floodplain river systems: a review for the temperate zone. River Res Appl 21:719–737 Stromberg JC, Merritt DM (2015) Riparian plant guilds of ephemeral, intermittent and perennial rivers. Freshwat Biol 61:1259–1275 Tachet H, Richoux P, Bournaud M, Usseglio-Polatera P (2002) Freshwater invertebrates (French). 2nd edn. CNRS Éditions, Paris Tang SM, Montgomery DR (1995) Riparian buffers and potentially unstable ground. Environ Manage 19:741–749 Thioulouse J, Chessel D, Dolédec S, Olivier JM (1997) ADE-4: a multivariate analysis and graphical display software. Stat Comput 7:75–83 Webb CT, Hoeting JA, Ames GM, Pyne MI, Poff NL (2010) A structured and dynamic framework to advance traits-based theory and prediction in ecology. Ecol Lett 13:267–283 Zuloaga FO, Morrone O (1996) Catalog of vascular plants of the Argentine Republic. I. (Spanish). Pteridophyta, Gymnospermae and Angiospermae (Monocotyledoneae). Monogr Syst Bot Missouri Bot Gard 60:1–323 Zuloaga FO, Morrone O (1999) Catalog of vascular plants of the Argentine Republic. II. (Spanish). Angiospermae (Dicotyledoneae). Monogr Syst Bot Missouri Bot Gard 64:1–1269 Zuloaga FO, Nicora EG, Rúgolo de Agrasar ZE, Morrone O, Pensiero JF, Cialdella AM (1994) Catalog of the Poaceae family in the Argentine Republic (Spanish). Monogr Syst Bot Missouri Bot Gard 47:1–178 Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformation.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Dec, 2025 Reviews received at journal 07 Dec, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers invited by journal 04 Nov, 2025 Editor assigned by journal 28 Oct, 2025 Submission checks completed at journal 04 Oct, 2025 First submitted to journal 03 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7775825","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":543475754,"identity":"70670944-1a98-4922-844e-128f093d9e3c","order_by":0,"name":"Edgardo Javier Ignacio Pero","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYFCCBCBmg7I/gAjmAwwMPMRqYZwBItkSSNDCzEOMFn729IufK8psGMzZex8+tm27k8/fxsD44G0bg7x5A3Ytkj1viiXPnEtjsOw5bmyc2/bMcsYxBmbDuW0MhnMOYNdicCMnQbKx7TCQkcYmndt22IDhfgObNG8b1GNYgP2NnOSfYC33n7FJWwK1yB9jYP8N1GKPS4uBRPoxqC1sbNKMQC0GxxjYmIFaEnFpkTjzhs2y4Vwaj2VPGrNhz7nDBobHGJsl55yTSMalhb89/fHNhjIbOXP2Y4wPfpQdNpA7xnzww5syG1tcWoBRYIAgIYCxAWQ9Tg0MDOwPIJ7Co2QUjIJRMApGOAAAw3pV3NpIF9kAAAAASUVORK5CYII=","orcid":"","institution":"Centro de Investigacion y Transferencia (CIT)","correspondingAuthor":true,"prefix":"","firstName":"Edgardo","middleName":"Javier Ignacio","lastName":"Pero","suffix":""},{"id":543475755,"identity":"de38f9a4-322a-4ed9-9e66-82f495479d7e","order_by":1,"name":"Mayra Alejandra Piccinetti","email":"","orcid":"","institution":"Instituto de Biodiversidad Neotropical (IBN)","correspondingAuthor":false,"prefix":"","firstName":"Mayra","middleName":"Alejandra","lastName":"Piccinetti","suffix":""},{"id":543475756,"identity":"e7d0c757-23de-46d4-8fc8-fdc286c89bf3","order_by":2,"name":"María Celina Reynaga","email":"","orcid":"","institution":"Instituto de Biodiversidad Neotropical (IBN)","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Celina","lastName":"Reynaga","suffix":""}],"badges":[],"createdAt":"2025-10-03 19:08:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7775825/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7775825/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96244215,"identity":"69c9e22c-b5f9-4d73-b6a9-056efb3ee323","added_by":"auto","created_at":"2025-11-19 07:17:57","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":431564,"visible":true,"origin":"","legend":"","description":"","filename":"Maintextfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/88f3949d4facfa7cb450adf5.docx"},{"id":95935360,"identity":"532dcd53-082b-4b07-acf9-86c2274ff0e4","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3741116,"visible":true,"origin":"","legend":"","description":"","filename":"Fig1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/8405d7669058aa7990233a79.tiff"},{"id":95935362,"identity":"5cc8c36d-1567-45dc-b48b-413482b3ebed","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5758574,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/eb9787d88eb472bc7b103301.tiff"},{"id":95935355,"identity":"ce3bce61-593b-484e-bf3f-fd381c76b19b","added_by":"auto","created_at":"2025-11-14 15:23:41","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5735,"visible":true,"origin":"","legend":"","description":"","filename":"0da37d67a5f14aa1aa8350a6f8725957.json","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/f56f92c943cf9e35aeb16388.json"},{"id":95935433,"identity":"7e887da2-5cbf-4144-b03d-7a00dca8e7d8","added_by":"auto","created_at":"2025-11-14 15:23:45","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101912,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/8fba2e0a10332e9529980490.docx"},{"id":95935407,"identity":"3ac6531c-3ea4-40e9-9248-9a18a69b85b0","added_by":"auto","created_at":"2025-11-14 15:23:43","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126307,"visible":true,"origin":"","legend":"","description":"","filename":"0da37d67a5f14aa1aa8350a6f87259571enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/9a9b957b3f5d161e9bec6733.xml"},{"id":95935405,"identity":"6f3d886a-7fb6-4acc-a0aa-6e640308dfff","added_by":"auto","created_at":"2025-11-14 15:23:43","extension":"tiff","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3741116,"visible":true,"origin":"","legend":"","description":"","filename":"Fig1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/ddbd4edde624c9faac701b99.tiff"},{"id":95935356,"identity":"8d2b2c21-635b-4dee-a14f-f5822af5b02f","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"tiff","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5758574,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/565b4a08d4afcd96f8cbec97.tiff"},{"id":95935402,"identity":"0b6930cc-6899-4631-acd0-a442711fc363","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":249856,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/caed8dffd555bae0af56812f.jpeg"},{"id":95935415,"identity":"396151a5-e2b1-4cf2-84d5-83a78364cd0e","added_by":"auto","created_at":"2025-11-14 15:23:44","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":138252,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/070c4f51e1a1d1e3737bef09.png"},{"id":95935358,"identity":"47d61dc5-be07-4e16-873b-07b8e299b4f1","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":365569,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/e7932d4c72a69eb701ad2ffb.png"},{"id":95935409,"identity":"f35c43e9-9657-44be-92fb-1fc21ea5ae04","added_by":"auto","created_at":"2025-11-14 15:23:43","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96449,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/2e27ba6bc5db3e0bec0404ae.png"},{"id":95935412,"identity":"b2d8ef2c-72c7-4b4e-8e99-747742cc895b","added_by":"auto","created_at":"2025-11-14 15:23:43","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":369309,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/f2ed862ca81ebaa8ad405604.png"},{"id":95935352,"identity":"5bc9cd88-5c80-4fbf-94b4-dc4c180ea5c7","added_by":"auto","created_at":"2025-11-14 15:23:41","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":104918,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/7bb4a3066b7c42516d9a6414.png"},{"id":95935353,"identity":"8c4beeb7-9101-4c63-9340-cd69dbf6e79a","added_by":"auto","created_at":"2025-11-14 15:23:41","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":124574,"visible":true,"origin":"","legend":"","description":"","filename":"0da37d67a5f14aa1aa8350a6f87259571structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/5d2ad3f71cb1fbdab3357e66.xml"},{"id":95935354,"identity":"29fec71a-c6d2-4847-9342-ce9cac84cca3","added_by":"auto","created_at":"2025-11-14 15:23:41","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":130075,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/f3a92d66b3ca60f0dac5d452.html"},{"id":95935414,"identity":"41951d95-10a1-4225-a822-3d99571b826c","added_by":"auto","created_at":"2025-11-14 15:23:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2109334,"visible":true,"origin":"","legend":"\u003cp\u003eStudy area with location of sampling sites and a detailed image from each sampling site and the location of lateral transects (yellow lines). River water flows to the right or bottom of the image. Codes: Y Yungas forest, C Western Chaco. (Color figure online). Source: Pero and Quiroga (2019).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/3bd8ac782289e1541772c7ad.png"},{"id":95935350,"identity":"52e1c8cc-8f20-44a3-b65f-229a1d1f69af","added_by":"auto","created_at":"2025-11-14 15:23:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":709981,"visible":true,"origin":"","legend":"\u003cp\u003eProjection of the first factorial plane of the RLQ analysis showing separately the ordering of: left side up: environmental variables, left side down: sites, right side up: functional traits modalities, right side down: taxa.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/ce8f389bbcdd48813419072b.png"},{"id":96255302,"identity":"84cb3509-c73b-40dd-adbb-076f0bdf1c3f","added_by":"auto","created_at":"2025-11-19 07:48:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3530257,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/a0ce2e46-3f6e-4b4c-bf35-4431fe7ae162.pdf"},{"id":95935404,"identity":"9a0570c1-7e80-4486-8b94-9ffd7f35bec6","added_by":"auto","created_at":"2025-11-14 15:23:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":101912,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7775825/v1/5506fac1c394d7098610705b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analyzing biological traits of riparian forest along ecoregions and local habitats to define functional targets for their restoration at different scales","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRiparian forests are considered an interface between terrestrial and aquatic ecosystems and are among the most vulnerable environments to both climate change and human impact (Capon et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The importance of this land\u0026ndash;water interface has been emphasized for many reasons: they are extremely dynamic environments in terms of structure, function, and diversity, and they reinforce abiotic\u0026ndash;biotic feedbacks (Naiman et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Pokrovsky \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pinay et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to Naiman et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), riparian forest is defined as the vegetation directly adjacent to rivers and streams. This forest extends laterally from the active channel to the uplands, including active floodplains and the immediately adjacent terraces. Many authors have identified characteristic vegetation within riparian zones, with different compositions, structures, and functions from that of the adjacent vegetation (Gregory et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Naiman et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Tang and Montgomery \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Prach and Straskrabov\u0026aacute; \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Naiman and D\u0026eacute;camps \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). However, few studies over the last decades have quantified changes in riparian and adjacent forest relations across landscape units or ecoregions that have marked climatic or geographic differences (Pinnay et al. 1990; Naiman et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Cattaneo et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). In recent years, there has been a renewed interest in studying the relation between riparian vegetation and hydrogeomorphological processes from new conceptual frameworks (e.g., Steiger et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Corenblit et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), even though few studies have addressed this issue from a landscape perspective (Kim and Kupfer \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kujanova et al. 2018). Although riparian vegetation may vary in its structure and composition across different landscape units (Pero and Quiroga \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), it could be expected that the riparian communities share a set of functional traits among ecoregions regardless of their species identities.\u003c/p\u003e\u003cp\u003eFunctional traits of biological communities (strategies to maximize their fitness and survival in the face of different spatial and temporal characteristics of the habitat (Poff \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1997\u003c/span\u003e)) link community structure to ecosystem processes (Diaz et al. 2007; Webb et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). By moving beyond species identity, trait-based approaches also enable comparisons of communities across systems (Cadotte et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which allows better generalization of research results, and for example, to achieve functional targets for ecosystem restoration as a critical issue for effective mitigation of ecological degradation (Gornish et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Laughlin \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Merchant et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, in riparian zones, most of the previous studies using a functional approach have focused on a single environmental gradient such as, the flood gradient (Aguiar et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Bejarano et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; McCoy-Sulentic et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gaudichet et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), or to the effects of interactions between it and human-mediated environmental gradients (see e.g., Brummer et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dawson et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Janssen et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but no study has focused on traits variations along ecoregional gradients. Some studies analyzed traits variation in riparian areas along ecotones. For example, Lamb and Mallik (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) found that several traits, including deciduous leaves, wind and water-borne diaspore dispersal, wind pollination, rhizomatous clonal growth, nitrogen fixation, and the phalanx clonal growth form, all declined in prevalence from the streambank to the forest. Another group of traits, including vertebrate diaspore dispersal and ericoid mycorrhizae, displayed the opposite pattern, increasing in prevalence from the streambank to the forest. Kyle and Leishman (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), examined the patterns of plant functional trait variation in relation to geomorphology on three geomorphic surfaces (point bar, bench and bank) along the Upper Hunter River, Australia. They found that generally the point bar was associated with species that were herbaceous, with small seed mass, a short stature and a high specific leaf area (SLA). Conversely, the bench was associated with grasses that had unassisted seed dispersal and intermediate seed mass and SLA, while species on the bank had tall stature, large seed mass, a high SLA and a perennial life cycle.\u003c/p\u003e\u003cp\u003eIn subtropical rainforest and dry forest of Argentina, Pero and Quiroga (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) revealed that the riparian forest may be very different from the adjacent, mainly in species dominance. However, the hypothesis that differences between riparian and adjacent zones would be less marked in humid than semiarid regions was not supported by their results. Marked differences in geomorphological and physical streamside features were found between the ecoregions studied by Pero and Quiroga (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and they were strongly associated to assemblage distribution. It could be expected that riparian communities from contrasted ecoregions such as the Yungas rainforest and Western Chaco dry forest share a set of functional traits among ecoregions regardless of their species identities. Furthermore, to incorporate functional targets in restoration processes, the functional structure of the reference model must be well known (Gann et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The region has a high deficit of riparian forest due to the changes in land uses that have occurred in recent decades (Pero et al. 2020a). A reference model was defined for rivers (Pero et al. 2020b) and riparian zones (Pero and Quiroga \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) of northwestern Argentina, but functional traits have not been included. Accordingly, the main objective of the present study was to analyze the functional structure (based on biological traits) of the riparian forest within local habitat and between the humid and semiarid ecoregions mentioned. Firstly, we analyzed the physical variables and the physiography of the streamside to compare the geomorphology among sites. Secondly, we compared the composition and structure of tree, bush, and liana species between the forest zones located next to the river and those located farther away. Thirdly, we compared functional dissimilarities in forest sectors between ecoregions to analyze variations across landscapes. Finally, we proposed a functional reference model for the regional restoration of riparian forest.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eStudy area\u003c/p\u003e\u003cp\u003eThe study area is located between 26\u0026ndash;28S and 66\u0026ndash;64W, including most of Tucum\u0026aacute;n province and their borders with Santiago del Estero province in Northwestern Argentina (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The area covers a wide zone with heterogeneous landscapes containing diverse ecosystems such as deserts, mountain cloud forests, dry forests, and grasslands (Brown and Pacheco \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In this study, we sampled streams located in two different ecoregions: The Yungas subtropical cloud forest and the Western Chaco dry forest. The Yungas subtropical cloud forest (Yungas forest) is a narrow belt of mountain rainforest that ranges from 400 to 3000 m a.s.l. (Brown \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The Yungas forest is part of a long chain of mountain cloud forests that extends along the east side of the Andes Mountains of South America from Venezuela to northwestern Argentina. The climate is warm and humid, with mean annual temperatures ranging from 14 to 26\u0026deg;C and rainfall from 1000 to 2500 mm (Hueck \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). The Yungas forest is stratified into three vegetation floors or bands. The high montane forest (1500\u0026ndash;3000 m a.s.l.) contains monospecific tree stands that are usually either \u003cem\u003eAlnus acuminata\u003c/em\u003e or \u003cem\u003ePodocarpus parlatorei\u003c/em\u003e. Rainfall reaches 1000 mm. The main human activity in this area is scattered cattle and fire to maintain pastures (Brown and Pacheco, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The low montane forest (700\u0026ndash;1500 m a.s.l.) has the most diverse vegetation, with many evergreen species, and is dominated by \u003cem\u003eCinnamomum porphyrium\u003c/em\u003e and \u003cem\u003eBlepharocalyx salicifolius\u003c/em\u003e. The low montane forest also has the highest precipitation (2000 mm annually) and the least seasonal hydrological regime. The foothill forest (400\u0026ndash;700 m a.s.l.) contains deciduous trees and is dominated by \u003cem\u003eTipuana tipu\u003c/em\u003e and \u003cem\u003eEnterolobium contortisiliquum\u003c/em\u003e. The annual rainfall on this floor varies between 1000\u0026ndash;1500 mm during the wet season, and the 6-month dry season (50 mm rainfall) extends from June to November (Brown et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This area is the one, most widely modified by human activities at present, with the main urban centers and industrial activities (sugar and citrus) located in it (Brown and Pacheco, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The Western Chaco ecoregion is a vast sedimentary fluvial plain formed by the streams or rivers that run northwest to southeast and includes parts of northwestern Argentina, southeastern Bolivia, northwestern Paraguay, and southwestern Brazil (Great South American Chaco). The headwaters are located in the mountains, outside the region to the west, and they transport great quantities of sediments into the region. Mean annual temperatures range between 19 and 24\u0026deg;C. Mean annual rainfall varies between 400 and 900 mm, with most precipitation falling in the summer and little falling in the winter (Minneti \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The vegetation is composed of dry forests and segregated grasslands. This ecoregion is classified into three sub-ecoregions: Arid Chaco, Semiarid Chaco, and Chaco Serrano (Brown and Pacheco \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Only the latter two are represented in the study area. The Chaco Serrano is part of the western border of the ecoregion and is characterized by low mountain topography. It is bordered in some places by the Yungas forest. The Semiarid Chaco occupies the greater portion of the ecoregion and is a continuous xerophytic and semi-deciduous forest. A wide transition zone occurs between the Western Chaco and the Yungas forest, which includes species common in both ecoregions (Cabrera \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1976\u003c/span\u003e), although it is currently highly modified by agricultural use (Gasparri \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSampling design and methods\u003c/p\u003e\u003cp\u003eTen sites were surveyed, each consisting of a stream or river reach of around 100 m in length (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Four sites were located in the Yungas forest ecoregion (Apeadero Mu\u0026ntilde;oz [High montane forest], Las Conchas [Low montane forest], and El Sonador streams and Pueblo Viejo river [Foothill forest]) and the other six in the Western Chaco ecoregion (Tala and Sal\u0026iacute; [Chaco Serrano] and Chico, Marapa, and two sites in Urue\u0026ntilde;a river [Semiarid Chaco]) (geographic coordinates in Online Resource 1). All the sites selected were minimally impacted by human activities and were designed as reference sites for ecoregions (Pero et al. 2019; Pero and Quiroga, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and river types (Pero et al. 2020). Nevertheless, the sites located in Western Chaco were closer to human settlements and had some sign of cattle presence in the area, such as dung. A block design was performed to minimize the differences among sites in the analyzes (Feinsinger \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Three longitudinal transects randomly distributed (left or right riparian margin) and situated in a perpendicular direction from the stream or river channel were surveyed in each sampling site (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each transect was divided into sampling units (SU) of 5 m in length and 1 m in width, totaling 10 SU per transect. The first four SU (0 to 20 m) were considered a priori as the \u0026lsquo;\u0026lsquo;riparian forest\u0026rsquo;\u0026rsquo; sectors closest to the water course and the last four (30 to 50 m) were considered the \u0026lsquo;\u0026lsquo;adjacent forest\u0026rsquo;\u0026rsquo; sectors distant from the water course. The middle SU (20 to 30 m) were considered a buffer area between forest sectors and were therefore not included in the analyzes (Feinsinger \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The composition and structure of riparian and adjacent forests were surveyed through transects, totaling 120 m\u003csup\u003e2\u003c/sup\u003e surveyed in each site (60 m\u003csup\u003e2\u003c/sup\u003e per forest sector). In each transect, the identity, basal area (calculated using diameter at breast height, DBH) and height of each tree, bush, liana, and fern individual were registered. Only specimens with more than 50 cm in height and 1 cm in DBH were considered. Specimens were identified to species level following the South American catalog for vascular plants (Zuloaga et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Zuloaga and Morrone 1996; Zuloaga and Morrone 1999). All species found were listed in a table (Online Resource 2). In addition, at each transect, the lateral slope of the river margins was measured using a clinometer, which was aligned between two distant objects (1-m-high sticks) every 10 m to produce a physiographic lateral view of the margins. A longitudinal slope was obtained from a digital elevation map (ASTER DEM 30x30 m resolution) and calculated using Geographic Information Systems (GIS) software (QGIS 2014). The widths of the wet channel and floodplain (the area between the wet channel banks and the base of the enclosing valley walls, Naiman et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) were measured with a metric ruler in each site. Site C6 was not completed and only two transects were surveyed in it due to climatic conditions during the sampling work. Site Y4 had a canyon-constrained reach and it was therefore very difficult to survey the adjacent forest sectors completely. Sampling was carried out during October 2015 and May 2016.\u003c/p\u003e\u003cp\u003eFunctional traits definition\u003c/p\u003e\u003cp\u003eThe definition of the biological traits of the organisms consists of identifying the characteristics that carry some ecological significance (Tachet et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). It includes the different modalities or forms that a trait can take, established mainly by its ability to use environmental resources, overcome environmental stress, etc. For this study, ten biological traits were defined, with their respective modalities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Traits were assigned to each species using various sources, including: (1) regional floras (Digilio and Legname \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1966\u003c/span\u003e); (2) botanical monographs; (3) different databases: the BIOLFLOR trait base (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www2.ufz.de/biolflor/\u003c/span\u003e\u003cspan address=\"http://www2.ufz.de/biolflor/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e index.jsp); TRY database (Kattge et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, public data only); Kew Database. Royal Botanic Gardens Kew 2016, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://data.kew.org/sid/\u003c/span\u003e\u003cspan address=\"http://data.kew.org/sid/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; eHALOPH \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sussex.ac.uk/affiliates/halophytes/;LEDA\u003c/span\u003e\u003cspan address=\"https://www.sussex.ac.uk/affiliates/halophytes/;LEDA\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://uol.de/en/landeco/research/leda;FLOWBASEhttps://www.isa.ulisboa.pt/proj/flowbase/\u003c/span\u003e\u003cspan address=\"https://uol.de/en/landeco/research/leda;FLOWBASEhttps://www.isa.ulisboa.pt/proj/flowbase/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; and (4) field observations. Some traits such as height and life form were obtained by direct observation of specimens at the field. The table of biological traits was built using fuzzy coding, which denotes the degrees of affinity exhibited by each taxon towards each feature modality (Online Resource 3). Value 0 is assigned in case of zero affinity of the taxon for a given modality, as opposed to the value 1, which indicates unequivocal affinity towards the modality in question (Chevenet et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFunctional traits and their modalities.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFunctional trait\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModality\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight (m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC1 (0,5\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC2 (2\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC3 (5\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC4 (10\u0026ndash;20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeaf type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSimple\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePinnate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBipinnate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrifoliate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeafless\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeaf form\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLanceolate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElliptical\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOblong\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOvate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLinear\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeaf size (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall (\u0026lt;\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium (3\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge (\u0026gt;\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife form\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTree\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShrub\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLiana\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHerbaceous\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFleshy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit size (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery small (\u0026lt;\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium (3\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge (\u0026gt;\u0026thinsp;6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDispersion type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutochory\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHydrochory\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnemochoral\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZoochory\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFenology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvergreen\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeciduous\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlowering period\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSummer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutumn\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWinter\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpring\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFructification period\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSummer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutumn\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWinter\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpring\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWood density (g/cm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow (0\u0026ndash;0,4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium (0,4\u0026thinsp;\u0026minus;\u0026thinsp;0,7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh (\u0026gt;\u0026thinsp;0,7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo wood\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eThe study of the relationships between vegetation and its environment involves the analysis of two tables: a taxonomic table, which expresses the taxon abundances in sampling units, and the environmental table that records quantitative values or categorical of environmental characteristics associated to the same units. A third table arranges data on traits distributed among the different taxa. Guided by the concept of Habitat Templet, it is intended to relate to the features biological with the environmental conditions where/are frequent; that is, it is necessary to cross the information contained in the preceding tables: 1) sampling units x environmental variables (environmental table R), 2) taxa x units of sampling (taxonomic table L), and 3) taxa x biological traits (biological traits table Q). The statistical technique that allows the ordering of the three tables of interest is the RLQ analysis (R mode; Q-mode; and L-link between R and Q), described by Doledec et al. (1996). The variables contained in R and Q can be qualitative and/or quantitative. The sampling units (SU) have been made to correspond to space-time units study (i.e., a particular site surveyed in a defined date), thus obtaining a total of 20 SUs. A correspondence analysis was performed (CA) on the taxonomic table L with its values of abundance previously log-transformed (x\u0026thinsp;+\u0026thinsp;1) to access a simultaneous sort of SUs and supporting taxa. The effect of the transformation was to smooth out the differences in abundance between dominant and rare taxa. The analysis of the environmental table R was carried out with a Hill-Smith (AHS) analysis (Hill and Smith \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1976\u003c/span\u003e), which is suitable for mixed situations in which they combine qualitative and quantitative variables. Finally, a correspondence analysis was used (ACF) (Chevenet et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) to explore the table of traits Q. For the purposes of investigating the joint structure of the three legal systems previously performed (AC, AHS and ACF) are applied the RLQ analysis, which allowed deducing the relationship between biological traits and environmental variables. The significance of the co-structure pattern between tables was examined using a non-parametric test based on 1000 random permutations of the rows, both of R as of Q. Analyzes and graphs were performed with the ade4 package (Thioulouse et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Dray and Dufour 2007) of the R environment (version 2.7.2) for mathematics and statistics (Ihaka and Gentleman \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; R Development Core Team 2008).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 91 plant species were identified in the study sites (Online Resource 2). The first two axes of the RLQ analysis represented 91.2% and 4.5%, respectively, of the total inertia of the cross table of environmental characteristics and biological traits (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The permutation test was significant for 1000 random realizations (P\u0026thinsp;=\u0026thinsp;0.009). The variances were compared obtained by the RLQ analysis with respect to the individual analyzes to obtain the percentage of representation of them in the global analysis: 1) the first axis of the RLQ decomposition captures 99.8% of the variability of environmental characteristics in the separate Hill-Smith analysis (R/RLQ), 2) a correlation was found between the flora table and the first RLQ axis. This value can be compared with the maximum value correlation between sites and taxa given by the square root of the first eigenvalue of AC (\u0026#120582;=0.781). Thus, the first RLQ axis explains 61.8% of the variability contained in the floral table L (L/RLQ). 3) Variability found for biological traits by the first axis of RLQ, in relation to the obtained by the individual ACF analysis, is 75.5% (Q/RLQ). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the results obtained from the RLQ analysis. Wet channel width and floodplain width were the environmental variables associated negatively to the first axis of analysis, while longitudinal and lateral slopes do in a positive way.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRLQ analysis summary. Eig\u0026thinsp;=\u0026thinsp;eigenvalues.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRLQ analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEig 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEig 2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance percentage (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91,22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR/RLQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEig 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEig 1\u0026thinsp;+\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance percentage (%) (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL/RLQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEig 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEig 2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance percentage (%) (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ/RLQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEig 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEig 1\u0026thinsp;+\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariance percentage (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66,2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe combined analysis between environmental variables, biological traits and taxa allows us to distinguish three main groups. By one side (negative axis 1), present sites that have higher longitudinal and lateral slopes, all of them from Yungas ecoregion. Trait modalities associated to that group of sites were height between 10 and 20 meters, large leaf size and elliptical form, evergreen leaf phenology, flowering and fructification period in winter (\u003cem\u003ePsycotria carthagenensis\u003c/em\u003e, \u003cem\u003eOcotea porphyria\u003c/em\u003e, \u003cem\u003eJuglans australis\u003c/em\u003e). On the other side (positive axis 1), present sites that have higher wet channel and floodplain width, mainly from Dry Chaco ecoregion. Trait modalities associated to that group of sites were height between 2 and 5 meters, lanceolate leaf form, the dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, low woody density (\u003cem\u003eSalix humboldtiana, Tessaria integrifolia, T. dodoneifolia, Erythrina crista-galli, Sapium haematospermun, Tamarix rammosissima\u003c/em\u003e). An intermediate group can be distinguished at the intersection of the axes and present the sites that are located at the foothills and transition zone between Yungas and Chaco ecoregion. A variety of trait modalities were associated to this group, but the most prominent are medium leaf size, leafless, liana and herbaceous life form, fleshy fruit type, and zoochory dispersal syndrome.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePhysical variables and the geomorphology of the streamside markedly influenced the distribution of taxonomical and functional features of species among forest sectors. A set of functional traits modalities related to a set of species were associated mainly with physical variations across ecoregions. In addition, differences between local forest sectors (riparian and adjacent) were less marked than those along ecoregions. Three main groups of sites were identified from the combination of environmental, taxonomical and functional characteristics. One group of sites were characterized by boxed margins in mountain forest, another group by lowland areas with wider floodplains and channels, and an intermediate group that included foothill areas. Therefore, an ecoregional and geomorphological gradient was evidenced. We couldn\u0026acute;t differentiate a common set of functional traits modalities in riparian communities from the contrasted ecoregions analyzed. Hence, the hypothesis that riparian zones share functional traits among ecoregions regardless of their species identities was not supported by the obtained results.\u003c/p\u003e\u003cp\u003eAlthough riparian zones did not share a set of functional traits modalities across ecoregions, some functional characteristics could be associated to the dimensions of riparian areas. For example, intermediate height, lanceolate leaf form, the dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, and low woody density were mainly related to wider floodplains and channels, where species associated to riparian zones where located (Pero and Quiroga \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hence, that assembly of species could be considered as a specific guild for riparian zones with wider floodplain and wet channel habitats (Merritt et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Stromberg and Merritt \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Coincidently, another study found that several traits, including deciduous leaves, wind and water-borne diaspore dispersal, and wind pollination, all declined in prevalence from the streambank to the forest (Lamb and Mallik \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Similarly, Kyle and Leishman (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) revealed that herbaceous species, with a short stature and a high specific leaf area (SLA) were associated with point bars of river channels, while tall stature and perennial life cycle species were associated with streambanks. In addition, other trait modalities were associated to intermediate sites where floodplain and wet channel were narrower, such as fleshy fruit type, and zoochory dispersal syndrome, as it was observed by Lamb and Mallik (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), where vertebrate diaspore dispersal increased in prevalence from the streambank to the forest.\u003c/p\u003e\u003cp\u003eThe knowledge acquired about the functional structure of riparian vegetation throughout the ecoregions studied is essential to better understand ecological processes in riparian areas. Some interesting relations were observed between ecological-response traits (Diehl et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and geomorphological features of riparian sectors. For example, the relation between a relative intermediate height, lanceolate leaf form, and low wood density with wider floodplain and channel areas could reflect plants adaptations to water availability and fluvial disturbances (Merritt \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Similarly, Stromberg and Merrit (2015) found that leaf length and wood density were inversely related and that plants with lower wood density had affinities to wetter habitats and were less tolerant of drought stress (Diehl et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In addition, knowing the structure of morphological-effect traits of riparian vegetation will allow us to better understand its influence on geomorphological processes (geomorphic functions) (Diehl et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Accordingly, it would be important to analyze other type of traits that influence the flow of water, transport of sediment, and stabilization of landforms, such as root architecture and root depth, because determines the plants ability to draw alluvial water and influences stream-bank and bar stability (Pollen-Bankhead and Simon \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Furthermore, knowing better the functional characteristics of riparian ecosystems is essential for the conservation, restoration and management of these threatened environments. For instance, a response-and-effect trait framework can generate assemblages of indigenous species to achieve desired community responses and/or achieve desired effects on ecosystem functions (Laughlin \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Merchant et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gornish et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn summary, although a group of common functional traits may not be identified in the vegetation of riparian zones, it is possible to associate some plants' functional characteristics with the dimensions of riparian areas. Therefore, knowing this group of functional traits and species associated with the different habitats or types of environments on the riparian zones will allow better definition of conservation and restoration goals including the heterogeneity found in these ecosystems. The results are important to better understand the ecological processes that occur in riparian areas, for example, those related to water or flood regulation, biogeomorphological processes related to erosion control, or seed dispersal and the provision of habitat and food for other organisms. Knowing better the functional structure of these communities in reference sites will allow us to improve the conservation and restoration of riparian environments to maintain and recover their functions (Gann et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.J.I.P. conceived the research idea; E.J.I.P. and M.P. collected data; M.C.R. performed statistical analyses; E.J.I.P., with contributions from M.P. and M.C.R., wrote the paper; all authors discussed the results and commented on the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are grateful to Sofia Malcum, Mario Feylling, Nicolas Laguna, Sebastian Albanesi, Guillermo Hankel, Dante Loto, and Carlos Navarro for their assistance in sampling trips; to Luciana Cristobal for helping to edit the image of the study area. This work was supported by Grants from the National Agency I+D, Argentina (PICT 2020-2447 and 2021-0058) and doctoral and postdoctoral scholarships from the National Council of Scientific and Technical Research (CONICET, Argentina).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAguiar FC, Cerdeira JO, Martins MJ, Ferreira MT (2013) Riparian forests of Southwest Europe: are functional trait and species composition assemblages constrained by environment? J Veg Sci 24:628\u0026ndash;638. https://doi.org/10.1111/jvs.12009\u003c/li\u003e\n\u003cli\u003eBejarano MD, Nilsson C, Aguiar FC (2017) Riparian plant guilds become simpler and most likely fewer following flow regulation. J Appl Ecol 55:365\u0026ndash;376. https://doi.org/10.1111/1365-2664.12949\u003c/li\u003e\n\u003cli\u003eBrown AD (2000) Development threats to biodiversity and opportunities for conservation in the mountain ranges of the upper Bermejo river basin, NW Argentina and SW Bolivia. Ambio 29:445\u0026ndash;449 https://doi.org/10.1579/0044-7447-29.7.445\u003c/li\u003e\n\u003cli\u003eBrown AD, Grau HR, Malizia LR, Grau A (2001) Argentina. In: Kapelle M, Brown AD (eds) Neotropical Cloud Forests (Spanish). INBio, Heredia, Costa Rica, pp. 623\u0026ndash;659\u003c/li\u003e\n\u003cli\u003eBrown AD, Pacheco S (2006) Proposal to update the ecoregional map of Argentina (Spanish). In: Brown A, Mart\u0026iacute;nez Ortiz U, Acerbi M, Corcuera J (eds) The Argentine environmental situation 2005. Fundaci\u0026oacute;n Vida Silvestre, Buenos Aires, pp. 28\u0026ndash;31\u003c/li\u003e\n\u003cli\u003eBrummer TJ, Byrom AE, Sullivan JJ, Hulme PE (2016) Alien and native plant richness and abundance respond to different environmental drivers across multiple gravel floodplain ecosystems. Divers Distrib 22:823\u0026ndash;835 https://doi.org/10.1111/ddi.12448\u003c/li\u003e\n\u003cli\u003eCabrera AL (ed) (1976) Argentine Phytogeographic Regions (Spanish). 2nd edn. Editorial Acme S.A.C.I., Buenos Aires\u003c/li\u003e\n\u003cli\u003eCadotte MW, Carscadden K, Mirotchnick N (2011) Beyond species: functional diversity and the maintenance of ecological processes and services. J Appl Ecol 48:1079\u0026ndash;1087 https://doi.org/10.1111/j.1365-2664.2011.02048.x\u003c/li\u003e\n\u003cli\u003eCapon SJ, Chambers LE, Mac Nally R, Naiman RJ, Davies P, Marshall N, Pittock J, Reid M, Capon T, Douglas M, Catford J, Baldwin DS, Stewardson M, Roberts J, Parsons M, Williams SE (2013) Riparian ecosystems in the 21st century: hotspots for climate change adaptation? Ecosystems 16:359\u0026ndash;381\u003c/li\u003e\n\u003cli\u003eCattaneo A, Salmoiraghi G, Gazzera S (1995) The rivers of Italy. In: Cushing CE, Cummins KW, Minshal GW (eds) River and stream ecosystems. Elsevier, Amsterdam, pp. 479\u0026ndash;505\u003c/li\u003e\n\u003cli\u003eChevenet F, Dol\u0026eacute;dec S, Chessel D (1994) A fuzzy coding approach for the analysis of long-term ecological data. Freshwat Biol 31:295\u0026ndash;309\u003c/li\u003e\n\u003cli\u003eCorenblit D, Tabacchi E, Steiger J, Gurnell AM (2007) Reciprocal interactions and adjustments between fluvial landforms and vegetation dynamics in river corridors: a review of complementary approaches. Earth Sci Rev 84:56\u0026ndash;86\u003c/li\u003e\n\u003cli\u003eCorenblit D, Davies NS, Steiger J, Gibling MR, Bornette G (2015) Considering river structure and stability in the light of evolution: feedbacks between riparian vegetation and hydrogeomorphology. Earth Surf Proc Land 40:189\u0026ndash;207\u003c/li\u003e\n\u003cli\u003eDawson SK, Warton DI, Kingsford RT, Berney P, Keith DA, Catford JA (2017) Plant traits of propagule banks and standing vegetation reveal flooding alleviates impacts of agriculture on wetland restoration. J Appl Ecol 54:1907\u0026ndash;1918. https://doi.org/10.1111/1365-2664.12922\u003c/li\u003e\n\u003cli\u003eD\u0026iacute;az S, Lavorel S, de Bello F, Qu\u0026eacute;tier F, Grigulis K, Robson TM (2007) Incorporating plant functional diversity effects in ecosystem services assessment. Proc Natl Acad Sci USA 104:20684\u0026ndash;20689 https://doi.org/10.1073/pnas.0704716104\u003c/li\u003e\n\u003cli\u003eDiehl RM, Merritt DM, Wilcox AC, Scott ML (2017) Applying functional traits to ecogeomorphic processes in riparian ecosystems. BioScience 67:729\u0026ndash;743 https://doi.org/10.1093/biosci/bix080\u003c/li\u003e\n\u003cli\u003eDigilio APL, Legname EP (1966) The indigenous trees of the province of Tucum\u0026aacute;n (Spanish). Opera Lilloana 15:1\u0026ndash;278\u003c/li\u003e\n\u003cli\u003eDol\u0026eacute;dec S, Chessel D, Ter Braak CFJ, Champely S (1996) Matching species traits to environmental variables: a new three-table ordination method. Environ Ecol Stat 3:143\u0026ndash;166\u003c/li\u003e\n\u003cli\u003eDray S, Dufour AB, Thioulouse J (2017) Package ade.4. Analysis of ecological data: Exploratory and Euclidean methods in environmental sciences. R-Project 20:31:18 UTC. https://pbil.univ-lyon1.fr/ADE-4\u003c/li\u003e\n\u003cli\u003eFeinsinger P (2001) Designing field studies for biodiversity conservation. Island Press, Washington DC\u003c/li\u003e\n\u003cli\u003eGann GD, McDonald T, Walder B, Aronson J, Nelson CR, Jonson J, Hallett JG, Eisenberg C, Guariguata MR, Junguo L, Hua F, Echeverr\u0026iacute;a C, Gonzales E, Shaw N, Decleer K, Dixon KW (2019) International principles and standards for the practice of ecological restoration. 2nd edn. Restor Ecol 27:1\u0026ndash;46\u003c/li\u003e\n\u003cli\u003eGasparri NI (2016) The transformation of land-use competition in the Argentinean Dry Chaco between 1975 and 2015. In: Niew\u0026ouml;hner J, Bruns A, Hostert P, Krueger T, Nielsen J\u0026Oslash;, Haberl H, Lauk C, Lutz J, M\u0026uuml;ller D (eds) Land use competition: ecological, economics and social perspectives. Springer, Berlin, pp. 59\u0026ndash;73\u003c/li\u003e\n\u003cli\u003eGaudichet C, Greulich S, Grelier S, Janssen P, Rodrigues S (2023) Influence of local environmental gradients on ecological strategies of herbaceous communities in riverine side channels. J Veg Sci 35:1\u0026ndash;16. https://doi.org/10.1111/jvs.13227\u003c/li\u003e\n\u003cli\u003eGornish ES, Campbell C, Svejcar L, Munson SM, Vaughn K, Spaeth MK, Yelenik SG, Wolf A, Mitchell R (2023) Functional traits are used in restoration practice: a response to Merchant et al. (2022). Restor Ecol 31:e13880\u003c/li\u003e\n\u003cli\u003eGregory SV, Swanson FV, McKee WA, Cummins KW (1991) An ecosystem perspective of riparian zones. BioScience 41:540\u0026ndash;551\u003c/li\u003e\n\u003cli\u003eHill MO, Smith AJE (1976) Principal component analysis of taxonomic data with multi-state discrete characters. Taxon 25:249\u0026ndash;255\u003c/li\u003e\n\u003cli\u003eHueck K (1978) The forests of South America. Ecology, composition and economic importance (Spanish). Sociedad Alemana de Cooperaci\u0026oacute;n T\u0026eacute;cnica (GTZ), Berlin\u003c/li\u003e\n\u003cli\u003eIhaka R, Gentleman R (1996) A language for data analysis and graphics. J Comput Graph Stat 5:299\u0026ndash;314\u003c/li\u003e\n\u003cli\u003eJanssen P, Pi\u0026eacute;gay H, Pont B, Evette A (2019) How maintenance and restoration measures mediate the response of riparian plant functional composition to environmental gradients on channel margins: insights from a highly degraded large river. Sci Total Environ 656:1312\u0026ndash;1335. https://doi.org/10.1016/j.scitotenv.2018.11.434\u003c/li\u003e\n\u003cli\u003eKattge J, B\u0026ouml;nisch G, D\u0026iacute;az S, Lavorel S, Prentice IC et al (2019) TRY plant trait database \u0026ndash; enhanced coverage and open access. Glob Change Biol 26:119\u0026ndash;188\u003c/li\u003e\n\u003cli\u003eKim D, Kupfer JA (2016) Tri-variate relationships among vegetation, soil, and topography along gradients fluvial biogeomorphic succession. PLoS ONE 11:e0163223. https://doi.org/10.1371/journal.pone.0163223\u003c/li\u003e\n\u003cli\u003eKujanov\u0026aacute; K, Matauskov\u0026aacute; M, Hosek Z (2018) The relationship between river types and land cover in riparian zones. Limnologica 71:29\u0026ndash;43\u003c/li\u003e\n\u003cli\u003eKyle G, Leishman MR (2009) Plant functional trait variation in relation to riparian geomorphology: the importance of disturbance. Austral Ecol 34:793\u0026ndash;804\u003c/li\u003e\n\u003cli\u003eLamb EG, Mallik AU (2003) Plant species traits across a riparian-zone/forest ecotone. J Veg Sci 14:853\u0026ndash;858\u003c/li\u003e\n\u003cli\u003eLaughlin DC (2014) Applying trait-based models to achieve functional targets for theory-driven ecological restoration. Ecol Lett 17:771\u0026ndash;784\u003c/li\u003e\n\u003cli\u003eMcCoy-Sulentic ME, Kolb TE, Merritt DM, Palmquist E, Ralston BE, Sarr DA, Shafroth PB (2017) Changes in community-level riparian plant traits over inundation gradients, Colorado River, Grand Canyon. Wetlands 37:635\u0026ndash;646\u003c/li\u003e\n\u003cli\u003eMerchant TE, Henn JJ, de Silva I, Van Cleemput E, Suding KN (2022) Four reasons why functional traits are not being used in restoration practices. Restor Ecol 31:e13788\u003c/li\u003e\n\u003cli\u003eMerritt DM (2013) Reciprocal relations between riparian vegetation, fluvial landforms, and channel processes. In: Shroder J (ed-in-chief), Wohl E (ed) Treatise on geomorphology: fluvial geomorphology. Elsevier, San Diego, pp. 219\u0026ndash;243. https://doi.org/10.1016/B978-0-12-374739-6.00239-6\u003c/li\u003e\n\u003cli\u003eMerritt DM, Scott ML, Poff LM, Auble GT, Lytle DA (2010) Theory, methods and tools for determining environmental flows for riparian vegetation: riparian vegetation\u0026ndash;flow response guilds. Freshwat Biol 55:206\u0026ndash;225\u003c/li\u003e\n\u003cli\u003eMinneti JL (1999) Climatic atlas of the Argentine Northwest (Spanish). Fundaci\u0026oacute;n Zon Caldenius, Tucum\u0026aacute;n\u003c/li\u003e\n\u003cli\u003eNaiman RJ, Beechie TM, Benda LE, Berg DR, Bisson PA, MacDonald LH, O\u0026rsquo;Connor MD, Olson PL, Steel EA (1992) Fundamental elements of ecologically healthy watersheds in the Pacific Northwest coastal ecoregion. In: Naiman RJ (ed) Watershed management: balancing sustainability and environmental change. Springer, New York, pp. 127\u0026ndash;188\u003c/li\u003e\n\u003cli\u003eNaiman RJ, D\u0026eacute;camps H (1997) The ecology of interfaces: riparian zones. Annu Rev Ecol Syst 28:621\u0026ndash;658\u003c/li\u003e\n\u003cli\u003eNaiman RJ, D\u0026eacute;camps H, Pollock M (1993) The role of riparian corridors in maintaining regional biodiversity. Ecol Appl 3:209\u0026ndash;212\u003c/li\u003e\n\u003cli\u003eNaiman RJ, D\u0026eacute;camps H, McClain ME (2005) Riparia. Ecology, conservation and management of streamside communities. Elsevier Academic Press, London\u003c/li\u003e\n\u003cli\u003ePero EJI, Quiroga PA (2019) Riparian and adjacent forests differ both in the humid mountainous ecoregion and the semiarid lowland. Plant Ecol 220:481\u0026ndash;498. https://doi.org/10.1007/s11258-019-00929-w\u003c/li\u003e\n\u003cli\u003ePinay G, Bernal S, Abbott BW, Lupon A, Mart\u0026iacute; E, Sabater F, Krause S (2018) Riparian corridors: a new conceptual framework for assessing nitrogen buffering across biomes. Front Environ Sci 6:47\u003c/li\u003e\n\u003cli\u003ePinay G, D\u0026eacute;camps H, Chauvet E, Fustec E (1990) Functions of ecotones in fluvial systems. In: Naiman RJ, D\u0026eacute;camps H (eds) The ecology and management of aquatic-terrestrial ecotones. Parthenon Publishing Group, Carnforth, pp. 141\u0026ndash;169\u003c/li\u003e\n\u003cli\u003ePoff NL (1997) Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. J N Am Benthol Soc 16:391\u0026ndash;409\u003c/li\u003e\n\u003cli\u003ePokrovsky OS (2016) Riparian zones: characteristics, management practices and ecological impacts. Nova Science Publishers, New York\u003c/li\u003e\n\u003cli\u003ePollen-Bankhead N, Simon A (2009) Enhanced application of root reinforcement algorithms for bank-stability modeling. Earth Surf Proc Land 34:471\u0026ndash;480\u003c/li\u003e\n\u003cli\u003ePrach K, Straskrabov\u0026aacute; J (1996) Restoration of degraded meadows: an experimental approach. In: Prach K, Jen\u0026iacute;k J, Large ARG (eds) Floodplain ecology and management. Academic Publishing, Amsterdam, pp. 87\u0026ndash;93\u003c/li\u003e\n\u003cli\u003eQGIS Development Team (2016) QGIS geographic information system\u003c/li\u003e\n\u003cli\u003eR Core Team (2019) R: a language and environment for statistical computing\u003c/li\u003e\n\u003cli\u003eSteiger J, Tabacchi E, Dufour S, Corenblit D, Peiry J-L (2005) Hydrogeomorphic processes affecting riparian habitat within alluvial channel-floodplain river systems: a review for the temperate zone. River Res Appl 21:719\u0026ndash;737\u003c/li\u003e\n\u003cli\u003eStromberg JC, Merritt DM (2015) Riparian plant guilds of ephemeral, intermittent and perennial rivers. Freshwat Biol 61:1259\u0026ndash;1275\u003c/li\u003e\n\u003cli\u003eTachet H, Richoux P, Bournaud M, Usseglio-Polatera P (2002) Freshwater invertebrates (French). 2nd edn. CNRS \u0026Eacute;ditions, Paris\u003c/li\u003e\n\u003cli\u003eTang SM, Montgomery DR (1995) Riparian buffers and potentially unstable ground. Environ Manage 19:741\u0026ndash;749\u003c/li\u003e\n\u003cli\u003eThioulouse J, Chessel D, Dol\u0026eacute;dec S, Olivier JM (1997) ADE-4: a multivariate analysis and graphical display software. Stat Comput 7:75\u0026ndash;83\u003c/li\u003e\n\u003cli\u003eWebb CT, Hoeting JA, Ames GM, Pyne MI, Poff NL (2010) A structured and dynamic framework to advance traits-based theory and prediction in ecology. Ecol Lett 13:267\u0026ndash;283\u003c/li\u003e\n\u003cli\u003eZuloaga FO, Morrone O (1996) Catalog of vascular plants of the Argentine Republic. I. (Spanish). Pteridophyta, Gymnospermae and Angiospermae (Monocotyledoneae). Monogr Syst Bot Missouri Bot Gard 60:1\u0026ndash;323\u003c/li\u003e\n\u003cli\u003eZuloaga FO, Morrone O (1999) Catalog of vascular plants of the Argentine Republic. II. (Spanish). Angiospermae (Dicotyledoneae). Monogr Syst Bot Missouri Bot Gard 64:1\u0026ndash;1269\u003c/li\u003e\n\u003cli\u003eZuloaga FO, Nicora EG, R\u0026uacute;golo de Agrasar ZE, Morrone O, Pensiero JF, Cialdella AM (1994) Catalog of the Poaceae family in the Argentine Republic (Spanish). Monogr Syst Bot Missouri Bot Gard 47:1\u0026ndash;178\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"vege","sideBox":"Learn more about [Plant Ecology](https://www.springer.com/journal/11258)","snPcode":"11258","submissionUrl":"https://submission.nature.com/new-submission/11258/3","title":"Plant Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"functional ecology, Yungas subtropical forest, Dry Chaco, dispersal syndromes, fluvial landscape, ecosystem restoration","lastPublishedDoi":"10.21203/rs.3.rs-7775825/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7775825/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRiparian forests perform a variety of functions but are among the most threatened environments. The objective of this study was to define functional targets for the restoration of riparian forest through an analysis of biological traits and its relationship with local geomorphological variables in Yungas subtropical forest and Dry Chaco Forest from northwestern Argentina. The composition and abundance of woody and herbaceous species were sampled. Twelve functional traits were characterized for 91 species based on field data and literature, which were ordered using fuzzy coding. According to RLQ analysis, three types of trait associations were identified: 1) Taller plants, large leaf size, elliptical form, evergreen phenology, flowering and fructification period in winter, associated to adjacent areas of greater slope and altitude, located in the Yungas forest; 2) Shorter plants, lanceolate leaf form, dispersal syndromes anemochory, autochory and hydrochory, flowering period in summer and fructification in autumn, low woody density, associated to greater channel width and flooding area and lower slopes, corresponding to the Dry Chaco; and 3) An intermediate group of sites that are located at the foothills and transition zone between ecoregions, with a variety of trait modalities, mainly medium leaf size, fleshy fruit type, and zoochory dispersal syndrome. Although a group of common functional traits may not be identified in the riparian zones, it was possible to associate some functional characteristics to the dimensions of riparian areas, helping to guide forest restoration targets along different landscape units, both in their species composition and in their functional structure.\u003c/p\u003e","manuscriptTitle":"Analyzing biological traits of riparian forest along ecoregions and local habitats to define functional targets for their restoration at different scales","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 15:23:17","doi":"10.21203/rs.3.rs-7775825/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-15T15:52:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T22:31:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45870886892204475070854080036795813398","date":"2025-11-06T22:44:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T15:30:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-28T18:43:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-04T06:39:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Ecology","date":"2025-10-03T18:52:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"vege","sideBox":"Learn more about [Plant Ecology](https://www.springer.com/journal/11258)","snPcode":"11258","submissionUrl":"https://submission.nature.com/new-submission/11258/3","title":"Plant Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3dd170a3-f937-4e6b-995e-ee47fc450a22","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T14:53:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 15:23:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7775825","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7775825","identity":"rs-7775825","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}