Disturbance regimes favor alternative plant communities in the natural grasslands of the Pampa Austral (Argentina)

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Predicting community responses to these changing conditions and designing appropriate conservation plans requires dissociating the individual contribution of each factor to community filtering. We ask whether fire, herbivory, temperature and drought, favor distinct communities in Pampean grassy ecosystems and which plant traits. Field surveys were conducted in three areas of the Ventania Mountain System in Pampa Austral (Argentina) exposed to varied fire, herbivory, and drought regimes. A total of 140 plant species were examined across 8 sampling areas, selected as representing different disturbance regimes. We measured 17 functional traits related to plant height, reproduction, and leaf area. The relationships between these traits and environmental variables were analyzed using RLQ and fourth-corner methods. RLQ analysis revealed that temperature, rainfall, and herbivory influenced plant communities, while fire frequency had less impact. We identified five distinct plant functional groups (PFGs) that differed in perenniality, type of pollination, resprouting capacity, spinescence, leaf hairiness and leaf area. Separating the effects of herbivory, fire, and drought reveals that multiple stresses could influence communities, resulting in higher resprouting and shorter life cycles. Analyzing how functional traits respond to environmental factors and disturbances provides insights into the conservation challenges posed by these changing disturbance dynamics in the Pampa biome. Functional traits Herbs Fire Grazing Drought Pampa Austral Natural grasslands Open ecosystems. Figures Figure 1 Figure 2 Figure 3 Introduction Although grassy ecosystems are the largest biome in the world, accounting for up to 40.5% of the terrestrial land area (Sala et al. 2017 ), the environmental drivers that affect their functioning and community filtering remain understudied. Grasslands are valued both for their high diversity and for the variety of ecosystem services they provide, including as sources of food, water catchments, recreational areas, and carbon sequestration and storage (Stevens et al. 2022 ). Because they are highly productive biomes, their value for conservation is often considered of lower priority, a large part of their domain is degraded and a very small proportion of their area is preserved (Stevens et al. 2022 ). The climatic conditions in many grassy ecosystems are not limiting for the establishment of woody species. This is revealed by the easy establishment of tree plantations in grassy landscapes (Veldman et al. 2015 ) and further questions which environmental factors are involved in keeping open large areas of grasses such as Pampean grasslands, a precondition for the survival of shade intolerant grasses and forbs that inhabit them (Bond 2019 ). Among the environmental drivers that have the potential to maintain grassy biomes open, grazing, fire, and seasonal drought play a preponderant role in modulating the composition and structure of communities (van Andel et al. 1987; Bond 2005 ). Although these factors have been shown to influence natural grassland dynamics, and are an integral part of their evolution and natural history (Strömberg 2011 ; Charles-Dominique et al. 2016 ), they often are considered as due to anthropogenic degradation and remain understudied as long-term drivers of vegetation and its evolution. Studying how disturbances shape grassy ecosystems communities is difficult since human activities have modified the intensity, extent and frequency of disturbance regimes and also have marked effects on the structure and function of grassland ecosystems (McIntyre and Lavorel 1994 ). For example, overgrazing by domestic livestock has been shown to both promote woody plants over grasses (Eldridge et al. 2011 ) and palatable over non-palatable grasses (Teague et al. 2016 ). Anthropogenic changes to the fire disturbance regime have also been shown to affect the dynamics of natural grasslands, leading to transitions from herbaceous to woody vegetation, with cascading consequences for soil and water resources that are critical to ecosystem functioning and the processes involved (Neary et al. 2020). For plants to persist in frequently disturbed systems, they need a particular suite of vegetative and reproduction traits that allow them to face frequent disturbances (McIntyre et al. 1999 ; Cornelissen et al. 2003 ). The Austral Pampas that comprise the orographic formation of Ventania, are the most productive natural grasslands in Central Argentina. One of the main economic activities in this area is cattle farming that has maintained the ecosystem in a state of continuous grazing since the 19th century (but with considerable intensification during the 20th century; Bilenca et al. 2004 ). Before European colonization and the establishment of cattle ranches, the main grazers were native ungulates, mostly pampas deer ( Ozotoceros bezoarticus ) and guanaco ( Lama guanicoe ) (Loponte et al. 2019). While the level of grazing of these native ungulates was assumed to be low, they likely contributed to the maintenance of the structure and composition of the natural grasslands (Medan et al. 2011 ). The replacement of native ungulates by domestic herbivores (cattle and horses) at constantly high stocking rates reduced the abundance of perennial forage grasses (Filazzola et al. 2020 ) thereby changing the composition and structure of natural grasslands (de Villalobos and Zalba 2010 ), among other effects (Loydi and Zalba 2009 ; Loydi et al. 2012 ). Additionally, the frequency and intensity of fires and droughts have increased in this region as a consequence of global climate change (Tiscornia et al. 2019 ; Paruelo et al. 2022 ) further affecting the historical disturbance regime. Over the last 20 years, the fire return interval in the Austral Pampas has decreased from one major fire every 7 years to one every 4 to 2 years (Brancatelli et al. 2020 ) and the seasonal droughts are now more severe and last longer (Michalijos 2019 ). The effects of these new disturbance regimes may combine and have potentially deleterious effects on grasslands (Neary et al. 2020). For example, combined with heat waves, the 2017 drought in central Argentina favored large-scale fire events that consumed grasses; the resulting food scarcity for domestic herbivores had consequences in the following year when unusually strong grazing pressure was exerted on the natural grasslands of the region (Bert et al. 2021 ). The influence of these novel disturbance regimes on herb communities is not fully understood. On one hand, they could represent a major threat to the natural functioning of open ecosystems if they create unprecedented environmental conditions for vegetation. On the other hand, they could act as mechanisms for opening, replacing historical disturbance regimes that were lost due to human activities, and could provide in-situ conservation opportunities to help maintain endemic species adapted to frequent disturbances (Yuan et al. 2016 ). For this reason, a comprehensive assessment of the effect of disturbances on plant communities in open ecosystems and the consequences of such disturbances for the native flora is required. Evaluating whether disturbances should be considered a threat or a conservation opportunity is a difficult task. Studying the community filtering driven by these novel disturbance regimes can provide valuable information to understand and manage open ecosystems better, as it reveals how each environmental variable affects groups of species with similar features. Species can be grouped according to ecological strategies related to their set of morphological, reproductive and phenological traits, (Semenova and van der Maarel 2000 ). The distribution of these ecological strategies along environmental gradients helps understand how disturbances and climate constrain plant communities and could provide guidance in designing appropriate conservation programs. Examining the community-level response to both natural and anthropogenic disturbances is crucial, given that native species are expected to persist and thrive best within a disturbance regime resembling the original ecosystem (McIntyre et al. 1999 ). On the other hand, species without the appropriate traits to persist would be expected to be filtered out from the communities (Díaz et al. 1998 ). One of the most significant challenges in studying the functional responses of species that thrive in frequently disturbed environments is identifying traits that effectively describe species survival and persistence after disturbance (Wigley et al. 2020 ). Among their desirable properties, these traits should promote the fitness of the species when subjected to a disturbance and should also be relatively easy to measure. Despite the specific composition and the climatic and edaphic characteristics of the grasslands, these traits could be utilized to identify changes in ecosystem functioning and aid in predicting anticipated changes in grasslands. In open ecosystems, such as natural grasslands, the interaction of multiple environmental filters acts as selective agents. Alteration in the disturbance regime modifies the functional structure of these grasslands, leading to the presence of species with specific traits that enable them to survive and persist in conditions of frequent disturbance and generate novel plant communities. To test this hypothesis, we conducted a simultaneous analysis of how primary climate drivers and the alteration of disturbance regimes, including fire, herbivory, temperature, and drought, function as filters for species traits selected to represent the vegetative and reproductive strategies of Pampean Austral communities. While most studies on plant responses to disturbances in the Pampean region have traditionally focused on specific plant functions (e.g., Candeias and Fraterrigo 2020 ) or on specific environmental gradients (e.g., Garnier et al. 2016 ), our approach involved characterizing 17 traits across 140 species and analyzing how these traits are filtered by fire, grazing, and drought using field experiences. We assessed the functional response of the grasslands in the Austral Pampa using RLQ and Fourth-corner methods. Below, we present a list of functional traits that can be used to assess the health of grasslands and discuss the relative impact of each disturbance on plant community assembly. Methods Study sites We recorded field characteristics in three areas of the Ventania mountains in the Pampean biogeographical province (Central Argentina). The climate of the study area is temperate, with an average annual temperature of 14° C and average precipitation of 800 mm, most of which falls in spring and fall, with occasional snow falls in winter (Michalijos 2019 ). The study area includes high plains (> 700 m.a.s.l.) composed of shallow rocky soils, piedmont grasslands and intermountain valleys both with consolidated soil (0.3 to 0.5 m depth) with superficial rocks (Long 2018 ). Three areas with intact grasslands were selected in a region that extends 150 km from south to north and 40 km from west to east (Guerrero and Apodaca 2022 ). The three areas (Fig. 1 ) were all selected because they include sites exposed to varying fire frequency, herbivory intensity and water stress during drought events: (a) the Ernesto Tornquist Provincial Park (ETPP) (38°03′00″S 62°02′00″W), a 6,700-ha-conservation area established in 1942 that contains the last relicts of Pampean grasslands in a relatively good state of conservation (Bilenca and Miñaro 2004); (b) the protected natural area Sierras Grandes (SGAP) (38°10′14″S 61°54′06″W), a 2,300-ha-conservation area established in 2013; (c) the Ceferino Hill (320 m.a.s.l.) that has neighboring piedmont grasslands (CHNG) (38°07′36″S 61°47′20″W). The two first areas have canyons that can protect a highly diverse vegetation (Long 2018 ) from strong winds, while the third area is composed of less rugged hills, exposed to drier and colder conditions (Cambarieri 2012 ). The three selected areas are similar in their geological and evolutionary history, making them comparable to each other (Demieri et al. 2005) The most abundant plants species are perennial tussock grasses, such as Nasella and Piptochaetium spp. and shrubs such as Discaria americana and Eupatorium buniifolium (Cabrera 1976 ). The native herbivorous pampas deer ( Ozotoceros bezoarticus ) and guanaco ( Lama guanicoe ) that were highly abundant in the Pampean grasslands in the pre-hispanic period are now either extinct or persist but at extremely low densities (Bilenca and Miñarro 2004). Over the course of the 18th century, these species were replaced by domestic livestock, cattle ( Bos taurus ) and horses ( Equus caballus ) (Modernel et al.,2016). Today domestic livestock are present in the two first areas, mainly horses in ETPP and cattle in SGAP (Giunti and Long 2018 ; Scorolli 2018 ), at a density higher than that recommended (0.15 UA) for Pampean Austral grasslands (Distel 2010 ) and are also present in the third area, but at lower densities. Fire frequency has been reported to have increased threefold compared to the historical record (Brancatelli et al. 2020 ) in the two first sites. In each area, we characterized the vegetation and species traits in eight sampling sites (Table 1 ): two grassy sites grazed by livestock, the first grazed mostly by cattle and the second mostly by horses, both without any occurrence of wildfires recorded for at least 20 years (Grazed: SG1 and SG2 respectively); two grassy sites subject to different fire frequencies, respectively every two years (SF1) and every four years (SF2), without domestic livestock grazing for at least 20 years; two drier grassy sites (located at higher altitudes), the first at 300 m above sea level (SD1) and the second at 400 m above sea level (SD2), both sites free from wildfires and domestic livestock grazing; and two grassy sites (as controls) in the vicinity of grazed sites but not grazed and where no fire has occurred in at least 20 years (SC1 and SC2) (Appendix S1). The distance between the study sites ranged from 5 to 25 km. Their topography and soil characteristics are described according to Demieri et al. (2005) and Kristensen and Frangi ( 2015 ). The soil depth of each sampling site was measured with a graduated soil auger. Temperature and precipitation data were obtained from the meteorological stations located closest to the experimental sites (INTA 2022) and their average annual values were calculated for the study period (2015–2019). Table 1 Properties and environmental characteristics of the study sites. Sampling sites: fire frequency, every two (SF1) and four years (SF2); drier conditions at 300 m.a.s.l. (SD1) and at 400 m.a.s.l. (SD2), and control sites not grazed or fire has occurred in at least 20 years (SC1 and SC2). Sampling sites Study Area Type of disturbance Surface area (hectares) Annual precipitation (mm) Mean temperature (°C) Soil depth SG1 ETPP Horses grazing (0.35 LSU) 10.0 847.60 14.0 Shallow SG2 SGAP Cattle grazing (0.25 LSU) 8.5 935.01 13.6 Deep SF1 ETPP Fires every two years 7.5 850.94 15.0 Shallow SF2 SGAP Fires every four years 5.5 894.98 14.9 Deep SD1 CHNG Drought 5.0 708.98 15.3 Rocky SD2 CHNG Drought 4.5 652.40 15.8 Rocky SC1 CHNG Control 6.5 830.55 15.3 Deep SC2 CHNG Control 5.5 945.28 13.5 Deep LSU: livestock units per hectare. The annual average precipitation and temperature were calculated for the sampling period (2015–2019). Soil depth: Shallow ( 0.15 m deep); Rocky: rocks visible on the surface. The classification by soil depth ranges is according to Imbellone et al. ( 2010 ). In each sampling site, we randomly distributed 20 plots (1 m2) and described their vegetation every spring and summer from 2015 to 2019. Each species was identified and its cover estimated using the Braun-Blanquet scale and the ordinal classes obtained were transformed into the average percentage covers of each class. We used for the analyses the average cover per species over the 5 years of sampling and species with less than 5% cover were not considered in the analyses (Krebs 2009 ). Species taxonomy and nomenclature were unified according to Zuloaga et al. ( 2019 ). Selection and characterization of functional traits We selected 17 categorical and numerical functional traits that provide information about the processes involved in the functional response of plant species to the conditions created by livestock grazing, frequent fires and drought (Table 2 ). Most traits were measured both in the field and in the laboratory; some were completed by information already available in databases and in the literature. All quantitative traits were measured on 5 individuals per species, randomly selected at each experimental site according to the criteria and methodologies proposed by Perez Harguindeguy et al. (2013). Plant height was measured in the field as the vertical height of the longest stem, branch or clump with a ruler, considering the surface of the ground as zero. We collected 10 fruits from each species and counted the number of seeds per fruit. Ten seeds were then harvested per plant and their length was recorded using a digital caliper. If the seeds were very small, they were measured under a binocular microscope. We counted the number of green leaves per plant on the three tallest stems of 5 randomly selected individuals per species. We compared leaf areas using the product of the width and length of 10 leaves on 3 stems of 5 individuals of each species, measured with a digital caliper. The average leaf area was multiplied by the average number of leaves recorded. Table 2 Description of the traits. Variables are either continuous (C) or categorical (F); the description and category of the variables of each functional trait are reported as V for vegetative and G for generative. Trait Type of variable Description Functional role Plant height C Vertical height (cm) of the longest stem, branch or clump measured from the surface of the ground V N° of seeds C Number of seeds per fruit G Size of seed C Length (cm) of at least 10 seeds per plant G N° of leaves C Number of leaves or blades of the tallest stems V Flower cluster F (single flower = 0; cluster of flowers = 1) Group of flowers arranged on a stem composed of a main branch or a complicated arrangement of branches G Perenniality F (annual or biannual = 0; perennial = 1) Survival for at least three growth cycles V Pollination F (entomophilous = 0; anemophilous = 1) Pollen dispersal by wind (anemophilous) or by insects (entomophilous) G Dehiscence F (fruit indehiscent = 0; fruit dehiscent = 1) Fruits with mechanism that allows the spontaneous release of seeds G Dormancy F (no dormant seeds = 0; dormant seeds = 1) Seeds with any mechanism that prevents germination G Animal dispersal F (other dispersing agents = 0); animal dispersal = 1) Fruit dispersal by animals (exo and endozoochory) G Spinescence F (without spines = 0; with spines = 1) Stem or leaf spines that hinder or prevent grazing V Leaf hairiness F (without hair = 0; with hair = 1) Leaves and stems have prolonged epidermal cells (trichomas) G Lateral exploration F (without stolons or rhizomes = 0; with stolons or rhizomes = 1) Stolons and rhizomes that promote lateral exploration and vegetative propagation V Storage organs F (without underground stems = 0; with underground stems = 1) Tubers, corms, rhizomes, bulbs, and other belowground stems that help the plant survive for long periods of time G Resprouting F (without capacity to resprouting = 0; with capacity to resprouting = 1) Capacity to activate dormant vegetative buds to produce regrowth V Erect habit F (no erect habit = 0; erect habit = 1) With upright main stem(s) V Leaf area F Surface area of the leaves or blades (cm 2 ) of the longest stems V The descriptions of functional traits are based on Perez Harguindeguy et al. (2013) and Wigley et al. ( 2020 ). Data Analysis We analyzed the relationships between functional traits and environmental variables using the RLQ and fourth-corner analyses using the vegan package (Oksanen et al., 2013) and ade4 package (Dray et al. 2007 ) all in R (version 3.0.2, R Core Team 2022). RLQ analysis links a matrix of environmental variables per site (R) to a species/traits matrix (Q) using the species/sites matrix (L) as a link. We applied a Hellinger transformation to the species distribution matrix to reduce the influence of hyper-dominant species in our analyses, and both the environmental variables and traits matrices were standardized to remove variable dimensionality. Fourth-corner analysis made it possible to test the associations between functional traits and environmental variables, and RLQ analysis provided an ordination to evaluate the overall significance of the species-traits-environment relationships (Dray 2014). Differences in the numerical and categorical variables between groups of species with similar combinations of traits were analyzed by one-way analysis of variance for a completely randomized design (Zar 2009 ). Prior to the analysis of variance of the cardinal data, we made an approximation of the binomial distribution to the normal distribution using a Poisson goodness-of-fit test, and the numerical data were transformed to the square-root. The means were separated using the Tukey test (Zar 2009 ). The data were analyzed using Real Statistics Resource Pack software (Release 7.6) (Zaiontz, 2021 ). Results We analyzed the relationships between plant traits and environmental variables in 140 plant species distributed in 31 families. The most represented families were Poaceae (21%) and Asteraceae (19%), followed by Fabaceae, Malvaceae and Caryophillaceae (5% each). This representation of families is comparable to that reported for the Pampa biome (Cabrera, 1976 ). Environmental factors related to past disturbances of the study areas had an impact on the function and structure of the plant communities (Fig. 2 ). Temperature, precipitation, frequency of fires and herbivory (total, by horses and by cattle) were positively or negatively correlated with at least one plant functional trait. Conversely, soil depth was not significantly correlated with any measured trait. We found significant relationships for the plant trait/environmental factors using RLQ analysis. The first two RLQ axes explained 92.68% of the cumulative projected inertia (75.06% Axis 1 and 17.62% Axis 2). The first RLQ axis was positively correlated (p < 0.05) with temperature and negatively correlated (p < 0.05) with total cattle and horse herbivory and rainfall while the second axis was positively correlated with rainfall and soil depth and negatively correlated with temperature; fire frequency was not a strongly structuring environmental variable (Fig. 3 B and Appendix S3). Plant traits positively correlated with (p < 0.05) the first axis were “perenniality” and “resprouting” while “leaf area” was negatively correlated (p < 0.05). “Anemophily”, “animal dispersal” and “erect habit” were positively correlated with the second axis (p < 0.05) while “leaf hairiness” and “spinescence” were negatively correlated with it (p < 0.05) (Fig. 3 B and Appendix S4). No strong relationships with the environmental variables were found for the remaining nine traits in our analysis (Fig. 3 B). The plant species were classified in functional groups based on their trait-environment scores in the RLQ analysis. The first two RLQ axes separated five ecologically differentiated functional groups (PFGs) of plants species with similar trait-environment responses (Fig. 3 A and 3 C). The five PFGs differed significantly in an ANOVA based on their scores in the RLQ analysis (Fig. 3 D): perenniality (F = 10.4; p = 6.2x10-09), type of pollination (F = 9.8; p = 10.5x10-08), resprouting capacity (F = 7.4; p = 0.0001), spinescence (F = 5.7; p = 0.0008), leaf hairiness (F = 3.2; p = 0.0221) and leaf area (cm2) (F = 12.4; p = 7.045x10-06). Seed dormancy and the number of seeds did not differ significantly between groups (ANOVA; F = 0.40; p = 0.8170 and F = 1.90; p = 0.1297 respectively). The five PFGs correspond to (Table 3 ): Table 3 Descriptions of the plant functional groups (PFG) identified. The number of species (S) in the group, the typical species and the dominant characters of each group are reported. PFG S Typical species Dominant characters 1 37 Abutilon terminale, Baccharis artemisioides, B. articulata, Dichondra sericea, Lucilia acutifolia, Margyricarpus pinnatus, Mimosa rocae Small perennial plants (< 0.20 m tall), with small hairy leaves, stem and root have sprouting capability and dehiscent fruits with numerous small seeds 2 47 Adesmia pampeana, Chaptalia integerrina, Eryngium nudicaule, Festuca pampeana, Gamochaeta filaginea, Helenium radianum, Holocheilus brasiliensis, Piptochaetium hackelii Perennial, annual and biannual plants, with erect, rosette and prostrate growth, mostly short herbs and tussock grasses 3 16 Aristida spegazzini, Bromus catharticus, Daucus pusillus, Erodium cicutarium, Geranium molle, Hordeum geniculatum, Hypochaeris glabra, Poa ligularis Annual or biannual plants (0.10–0.30 m tall), with rosette or erect growth and medium to large soft leaves, anemophilous pollination and dormant seeds 4 16 Cardus acanthoides, C. pycnocephalus, Echium plantagineum, E. vulgare Annual or biannual plants, frequently rosettes and with spines on either leaves or stems. Mostly weeds and pioneer plants 5 19 Chascolytrum brizoides, Koeleria ventanicola, Melica argyrea, Nasella neesiana, N. tenuis, Piptocaetium lejopodum, P. montevidense Tall perennial plants (0.20–0.60 m tall), with erect growth and anemophilous pollination, mostly tussock perennial grasses PFG1 - Drought tolerators: short statured species with small hairy leaves and high resprouting capacity. PFG2 - Generalists: species with intermediate trait values for all traits recorded and no clear functional specialization. PFG3 - Drought intolerants: crawling annual species with large leaves growing in sites with deeper soils and high water availability. PFG4 - Herbivore resistors and avoiders: either spiny species or species with a non-erect growth form (e.g., rosette or prostrate) that expose their leaves flat on the soil surface. PFG5 Herbivore-susceptible: tall, erect, perennial species with anemophilous pollination and fruits dispersed by animals. This group presents mostly species belonging to the "flechillar" community (perennial tussock grasses), typical of pristine grasslands in the Pampean region. Discussion The results of our analysis of the functional responses of 140 plant species using 17 functional traits, shows that the Austral Pampean grassland host communities function very differently. The communities respond differently to environmental factors that are currently impacted by global climate change and anthropogenic activities, which is creating novel climates and novel disturbance regimes. Drought and the herbivory regime were found to strongly influence plant communities in the Pampean region, in agreement with previous studies (Koerner and Collins 2014 ; Ratajczak and Ladwig, 2019 ), while changes in the historic fire record seemingly did not. Analyzing these factors together was important to be able to reveal their effects on the functional responses of Pampean communities. We now discuss how our findings provide the basis for more reliably predicting community responses to the consequences of climate change and anthropogenic activities, and how conservation and management practices could influence the emergence of unique community types in the Pampean biome. Disturbances promote alternative functional groups in Pampean grasslands While at first glance, Pampean grasslands may appear to be uniform as they share similar physiognomies, our analyses identified five functional groups of species with contrasted lifespans, pollination and dispersal, ability to resprout after disturbances, defenses, and drought adaptations on their leaves. Interestingly, the disturbance regime was important for the emergence of communities with distinct suites of trait and calls for conservation actions that manage the type, intensity and frequency of disturbance. Our control treatment, which corresponded to the exclusion of all disturbances, only promoted one of the five functional groups (PFG5) corresponding to perennial tussock grasses of the genera Nassella and Piptochaetium . Maintaining the high diversity of the Pampean grassy ecosystems therefore requires understanding the effect of disturbances and incorporating them in conservation actions. Effects of drought The most arid environments only enabled communities with small hairy leaves that produce numerous seeds germinating without dormancy (Fig. 3 ). Vegetation types with small hairy leaves are typically found in arid environments (Moles et al. 2020 ) as both traits help mitigate water losses during drought events (Seleiman et al. 2021 ). Species adapted to drier environments usually produce numerous seeds (Lorts et al. 2008 ), to secure persistence of the species by an effective dispersal that has a bigger chance of reaching wetter micro habitats. The lack of seed dormancy is not necessarily an advantage in the face of drought. Dormancy commonly helps avoid harsh seasons (dry or cold) and delays germination until conditions are more favorable for growth (Bewley et al. 2013 ). In the case of Pampa grasslands, the lack of dormancy of the functional group that survives well in the dry environment could be explained by seasonality, as the seeds are released during the fall wet season (Michalijos 2019 ) and could be one consequence of producing many seeds for which activating dormancy mechanisms could incur high costs. Effects of herbivory Pampean grasslands have been deeply modified by the presence of herbivores: the communities in sites exposed to herbivory are composed of a larger proportion of short annual species with spiny stalks or leaves and larger leaves. This distinct suite of traits encountered in areas exposed to mammalian herbivory is consistent with the results of previous works (e.g., Lavorel and Garnier, 2002 ; Borchardt et al. 2013 ; Lezama et al. 2014 ; Charles-Dominique et al. 2016 ; de Villalobos and Schwerdt 2018 ). Our analysis showed the effect of herbivory on community filtering to be particularly strong and confirmed that the presence of mammalian herbivores alters the vertical structure of the grasslands, as livestock tends to prefer taller species (Celaya et al. 2011 ; Zhang et al. 2020 ) and that the replacement of native herbivores such as guanacos by livestock can lead to major changes in composition, which, in some areas, could favor biological invasions in the Pampa biome (Chaneton et al. 2002 ; Loydi and Zalba, 2009 ; de Villalobos et al. 2011 ). Interestingly, understanding the effect of the novel herbivory regime in Pampa grasslands requires not only studying the effects of the density of herbivores compared to before the Hispanic herbivory regime but also the type of herbivory. Our results show that grazing by horses and cattle promoted different plant communities. Horse-grazed grasslands contain more plants with larger leaf areas (notably rosettes), whereas cattle-grazed grasslands contain spiny communities. The different communities that emerge in horse versus cattle grazed sites is probably related to the distinct preferences of the two herbivores. Horses tend to prefer perennial grasses with narrow leaves (Roger et al. 2014), thereby creating gaps that provide light for large leaf forbs and short statured woody species that require more light than grasses (Garnier et al. 2002 ). The promotion of forbs in grassy ecosystems by horses in mountain grasslands of the Austral Pampas was also reported by de Villalobos and Schwerdt ( 2018 ), and by Davies et al. (2019) in the Midwest of North America. Conversely, cows are more sensitive to spines and tend to select non-spiny species with higher nutritional quality, typically with a lower carbon-to-nitrogen ratio (Celaya et al., 2011 ; Pauler et al., 2020 ). The presence of native plant species with functional profiles that enable both horse and cattle herbivory, is first puzzling as it questions which herbivores could have selected for the species composing these communities in the pre-Hispanic period, and second, suggests that conservation programs in the Pampean region should find the right balance of herbivory (in terms of both the density and type of herbivore) to maintain the diversity of communities. Reduced effect of fire Surprisingly, fire frequency had little effect on filtering plant communities in our study sites. This suggests that all the functional groups of species in the Pampean grasslands we analyzed are resilient to fire, as even under high fire frequency, we did not observe a strong filtering effect, either at species or trait level. Concerning traits, only spinescence and seed dormancy (sub-significant) were associated with higher fire frequency, but not with other functional traits, such as resprouting capacity, which is commonly associated with fire-prone systems (Pausas et al. 2004 ; Clarck et al. 2013). Although seed dormancy has been suggested to promote fitness of plants in fire driven systems (Pausas and Lamont 2022 ) when dormancy is released by the fire generated heat and enable plants to exploit the post-fire environment with reduced competition (de Villalobos et al. 2007 ; Tangney et al. 2022 ), spinescence is not per se a fire adaptation. Spinescence is rarely expressed in fire-driven systems (Charles-Dominique et al. 2016 ) except in areas subjected to pyric herbivory, a disturbance regime in which both large mammalian herbivores are present and fires occur regularly, thereby promoting communities that are adapted to both disturbances (Fuhlendorf et al. 2009 ; Archibald et al. 2019 ). The fact spiny species are favored in frequently burned sites questions whether such a pyric herbivory regime could have driven Pampean communities in the past and calls for experimentation that combines the two types of disturbances to evaluate the effects of their combination. This would help design conservation programs adapted to the functioning of the Pampean flora. Alternatively, the absence of a clear functional profile of species in burnt sites could be related to species with higher levels of functional plasticity (not monitored in the present study) that, in turn, could promote persistence in areas with frequent fires (Simpson et al. 2019 ). The response of species to fire and their ability to resprout in the Austral Pampean grasslands may be influenced by complex interactions with a variety of factors, including fire intensity, and historical disturbance patterns. Such factors could modulate the relationship between fire and functional traits in a non-linear or context-dependent manner (Stephan et al., 2010 ). No differences were found between communities developing in sites with low (4-y-fire return interval) and high fire frequencies (2-y-fire return interval). Despite the increased occurrence of fires based on historical records in the study sites, it is possible that either these changes are too recent induce a community shift or that these fire frequencies fall within the expected frequency range that selected for the Pampas grassland ecosystems (Paruelo et al. 2022 ; Giorgi et al. 2020). Combined effects of different factors While our analysis did not consider interactions between factors, it is important to study simultaneously the main factors that could influence community dynamics and composition as it allows separating responses specific to a unique factor versus traits that could be promoted by varied alternative drivers. For example, our analysis showed that traits related to livestock grazing and drought conditions both favored plants with resprouting capacity and short life cycles. Several other studies showed traits similarly favoured by drought and grazing (Milchunas et al. 1988 ; Blumenthal et al. 2020 ; Irob et al. 2023 ): for example, deciduous leaves or short life cycles allow species to escape both drought and herbivory in the Austral Pampean grasslands. Short lived plants could complete their lifecycle swiftly during the wet season (Blonder et al. 2023 ) and efficient resource allocation could facilitate their regrowth and rapid reproduction after grazing (Hendrickson and Olson 2006 ). Blumenthal et al. ( 2020 ) also found that structural drought tolerance and avoidance traits were predictors of herbivore resistance in semi-arid shortgrass steppe and mixed grasslands in North America. Furthermore, Irob et al. ( 2023 ) reported that Namibian savannas with a higher proportion of herbivores were more resilient to drought. The co-occurrence of drought and herbivore adaptations could be related to the greater need of plants to defend themselves against herbivory when they grow in a more constraining environment where regrowth (and hence tolerance to damage caused by herbivory) is difficult (Grubb 1992 ). Our study emphasizes the significance of taking functional traits into consideration when investigating plant communities in the Pampa biome. Analyzing how these traits are influenced by environmental factors and disturbances led to a more comprehensive understanding of community functioning and responses to environmental changes. This knowledge is critical to develop effective conservation and management strategies to preserve biodiversity and ecological integrity in the Pampa biome. Additionally, our findings provide insights into the dynamics of plant communities over time and their responses to environmental disturbances in the Austral Pampean grasslands. By examining the relationships among functional traits, environmental factors, and disturbances, we can conclude that the grasslands of the Austral Pampean region possess adaptive capacity to variations in disturbances, as evidenced by a diverse array of species with functional traits. These findings pave the way for more sustainable management and call for further studies aimed at promoting the long-term resilience and stability of the Austral Pampean grasslands. Declarations Author Contribution A.E.V. designed the field experiment and collected the data. T. C.-D. developed the statistical analysis methods. Both authors analyzed the data, wrote the manuscript and contributed critically to the drafts and gave final approval for publication. Acknowledgements This work was funded by CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas) and SGCyT, (Secretaría General de Ciencia y Tecnología, Universidad Nacional del Sur, Argentina). 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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-4018818","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277157369,"identity":"78ffebe6-3a0a-4864-9f31-ac27fb9c6f07","order_by":0,"name":"Ana Elena de Villalobos","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie3RsQrCMBCA4SuFuqhdr0t9hUpBFPowCQVdHR0E61I35/oWguBcCbRL3OPWvoEgCC7FtKNorJtD/imE+zhCAHS6v8xYpwWMwZZH1lyk30mUEkBwovZEztTEk5NmK2InodyyRNfPzyWbL8HtC2LcFgqCgkqSoT/iM48lGfiOIKbDVWv4SRIL6VFYwLoW0L0gzcM+NmhIhfSQ1KSClSTmQ0W8fB2lNEa6R0l6MRBPEEu5ZdiQLfrIp8B2WxzueBlPVMRlnbK43gPX3mTmbX4PBv08ZBcVeQ2h/twfgE6n0+ne9QQuhlSUzkkZJgAAAABJRU5ErkJggg==","orcid":"","institution":"Universidad Nacional del Sur","correspondingAuthor":true,"prefix":"","firstName":"Ana","middleName":"Elena","lastName":"de Villalobos","suffix":""},{"id":277157370,"identity":"30a852b7-7981-4248-a429-76a376548ea0","order_by":1,"name":"Tristan Charles-Dominique","email":"","orcid":"","institution":"AMAP, Univ Montpellier, CIRAD, CNRS, INRAE, IRD","correspondingAuthor":false,"prefix":"","firstName":"Tristan","middleName":"","lastName":"Charles-Dominique","suffix":""}],"badges":[],"createdAt":"2024-03-06 00:17:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4018818/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4018818/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11258-025-01565-3","type":"published","date":"2025-09-10T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52448810,"identity":"206801c9-7e17-448c-83ce-62f988a91060","added_by":"auto","created_at":"2024-03-11 18:45:05","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1155349,"visible":true,"origin":"","legend":"\u003cp\u003eStudy areas: Ernesto Tornquist Provincial Park (A), Sierras Grandes protected natural area (B), Ceferino Hill (C) and neighboring piedmont grasslands (D).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4018818/v1/a426748fb9678e6c0ce5aa9e.jpeg"},{"id":52448808,"identity":"ec5d4c7c-1a3d-456f-9aeb-10e29f18a801","added_by":"auto","created_at":"2024-03-11 18:45:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":459786,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of associations between plant functional traits and environmental factors. Dark brown indicates a high positive correlation, dark blue a high negative correlation. Significant correlations are indicated by asterisks: * \u0026lt; 0.05; **\u0026lt; 0.01; ***\u0026lt; 0.001. Sub-significant relationships (with p-values between 0.10 and 0.05) are indicated by a dot. Dendrograms represent Ward agglomerative clustering on Euclidian distances between trait scores (dendrogram 1) and scores of environmental variables (dendrogram 2).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4018818/v1/25ecac35c4cf8cd8a1f8b1c4.png"},{"id":52448811,"identity":"391607ba-99cb-4495-8013-fe6506aa8fd3","added_by":"auto","created_at":"2024-03-11 18:45:05","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1152156,"visible":true,"origin":"","legend":"\u003cp\u003eTrait-environment relationships and functional groups. A. Dendrogram representing Ward agglomerative clustering. Functional groups (clusters) are indicated by different colors. B. Ordination from a RLQ analysis using data on species abundance, environmental variables and plant functional traits of experimental grasslands (Control, Fire, Grazing and Drought). Traits in bold letters presented significant (p \u0026lt; 0.05) weighted correlations with ordination axes. C. The position of the plant functional groups along the first two RLQ axes. Each dot represents one species, and their proximity indicates a similar trait-environment relationship. Functional groups (clusters) are indicated by different colors. D. Average categorical and numerical functional trait (+SD) between five plant functional groups (PFG). Columns with the same letter do not differ significantly (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4018818/v1/42c1c5eb268c61d387f021d9.jpeg"},{"id":91358986,"identity":"a4e093ea-d775-4c94-b781-3f91727cbe5c","added_by":"auto","created_at":"2025-09-15 16:03:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3463990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4018818/v1/faf4fa39-00b3-4434-8b10-c8bab088d14f.pdf"},{"id":52448807,"identity":"89882414-6504-4ed9-8613-84c47a21b79c","added_by":"auto","created_at":"2024-03-11 18:45:03","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21075,"visible":true,"origin":"","legend":"","description":"","filename":"SuportinginformationdeVillalobosCharlesDominique.docx","url":"https://assets-eu.researchsquare.com/files/rs-4018818/v1/0361dc64b5849ded38e88a0b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Disturbance regimes favor alternative plant communities in the natural grasslands of the Pampa Austral (Argentina)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlthough grassy ecosystems are the largest biome in the world, accounting for up to 40.5% of the terrestrial land area (Sala et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the environmental drivers that affect their functioning and community filtering remain understudied. Grasslands are valued both for their high diversity and for the variety of ecosystem services they provide, including as sources of food, water catchments, recreational areas, and carbon sequestration and storage (Stevens et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Because they are highly productive biomes, their value for conservation is often considered of lower priority, a large part of their domain is degraded and a very small proportion of their area is preserved (Stevens et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The climatic conditions in many grassy ecosystems are not limiting for the establishment of woody species. This is revealed by the easy establishment of tree plantations in grassy landscapes (Veldman et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and further questions which environmental factors are involved in keeping open large areas of grasses such as Pampean grasslands, a precondition for the survival of shade intolerant grasses and forbs that inhabit them (Bond \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among the environmental drivers that have the potential to maintain grassy biomes open, grazing, fire, and seasonal drought play a preponderant role in modulating the composition and structure of communities (van Andel et al. 1987; Bond \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Although these factors have been shown to influence natural grassland dynamics, and are an integral part of their evolution and natural history (Str\u0026ouml;mberg \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Charles-Dominique et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), they often are considered as due to anthropogenic degradation and remain understudied as long-term drivers of vegetation and its evolution.\u003c/p\u003e \u003cp\u003eStudying how disturbances shape grassy ecosystems communities is difficult since human activities have modified the intensity, extent and frequency of disturbance regimes and also have marked effects on the structure and function of grassland ecosystems (McIntyre and Lavorel \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). For example, overgrazing by domestic livestock has been shown to both promote woody plants over grasses (Eldridge et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and palatable over non-palatable grasses (Teague et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Anthropogenic changes to the fire disturbance regime have also been shown to affect the dynamics of natural grasslands, leading to transitions from herbaceous to woody vegetation, with cascading consequences for soil and water resources that are critical to ecosystem functioning and the processes involved (Neary et al. 2020). For plants to persist in frequently disturbed systems, they need a particular suite of vegetative and reproduction traits that allow them to face frequent disturbances (McIntyre et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Cornelissen et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Austral Pampas that comprise the orographic formation of Ventania, are the most productive natural grasslands in Central Argentina. One of the main economic activities in this area is cattle farming that has maintained the ecosystem in a state of continuous grazing since the 19th century (but with considerable intensification during the 20th century; Bilenca et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Before European colonization and the establishment of cattle ranches, the main grazers were native ungulates, mostly pampas deer (\u003cem\u003eOzotoceros bezoarticus\u003c/em\u003e) and guanaco (\u003cem\u003eLama guanicoe\u003c/em\u003e) (Loponte et al. 2019). While the level of grazing of these native ungulates was assumed to be low, they likely contributed to the maintenance of the structure and composition of the natural grasslands (Medan et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The replacement of native ungulates by domestic herbivores (cattle and horses) at constantly high stocking rates reduced the abundance of perennial forage grasses (Filazzola et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) thereby changing the composition and structure of natural grasslands (de Villalobos and Zalba \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), among other effects (Loydi and Zalba \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Loydi et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Additionally, the frequency and intensity of fires and droughts have increased in this region as a consequence of global climate change (Tiscornia et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Paruelo et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) further affecting the historical disturbance regime. Over the last 20 years, the fire return interval in the Austral Pampas has decreased from one major fire every 7 years to one every 4 to 2 years (Brancatelli et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the seasonal droughts are now more severe and last longer (Michalijos \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The effects of these new disturbance regimes may combine and have potentially deleterious effects on grasslands (Neary et al. 2020). For example, combined with heat waves, the 2017 drought in central Argentina favored large-scale fire events that consumed grasses; the resulting food scarcity for domestic herbivores had consequences in the following year when unusually strong grazing pressure was exerted on the natural grasslands of the region (Bert et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The influence of these novel disturbance regimes on herb communities is not fully understood. On one hand, they could represent a major threat to the natural functioning of open ecosystems if they create unprecedented environmental conditions for vegetation. On the other hand, they could act as mechanisms for opening, replacing historical disturbance regimes that were lost due to human activities, and could provide in-situ conservation opportunities to help maintain endemic species adapted to frequent disturbances (Yuan et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For this reason, a comprehensive assessment of the effect of disturbances on plant communities in open ecosystems and the consequences of such disturbances for the native flora is required.\u003c/p\u003e \u003cp\u003eEvaluating whether disturbances should be considered a threat or a conservation opportunity is a difficult task. Studying the community filtering driven by these novel disturbance regimes can provide valuable information to understand and manage open ecosystems better, as it reveals how each environmental variable affects groups of species with similar features. Species can be grouped according to ecological strategies related to their set of morphological, reproductive and phenological traits, (Semenova and van der Maarel \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The distribution of these ecological strategies along environmental gradients helps understand how disturbances and climate constrain plant communities and could provide guidance in designing appropriate conservation programs. Examining the community-level response to both natural and anthropogenic disturbances is crucial, given that native species are expected to persist and thrive best within a disturbance regime resembling the original ecosystem (McIntyre et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). On the other hand, species without the appropriate traits to persist would be expected to be filtered out from the communities (D\u0026iacute;az et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). One of the most significant challenges in studying the functional responses of species that thrive in frequently disturbed environments is identifying traits that effectively describe species survival and persistence after disturbance (Wigley et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among their desirable properties, these traits should promote the fitness of the species when subjected to a disturbance and should also be relatively easy to measure. Despite the specific composition and the climatic and edaphic characteristics of the grasslands, these traits could be utilized to identify changes in ecosystem functioning and aid in predicting anticipated changes in grasslands.\u003c/p\u003e \u003cp\u003eIn open ecosystems, such as natural grasslands, the interaction of multiple environmental filters acts as selective agents. Alteration in the disturbance regime modifies the functional structure of these grasslands, leading to the presence of species with specific traits that enable them to survive and persist in conditions of frequent disturbance and generate novel plant communities. To test this hypothesis, we conducted a simultaneous analysis of how primary climate drivers and the alteration of disturbance regimes, including fire, herbivory, temperature, and drought, function as filters for species traits selected to represent the vegetative and reproductive strategies of Pampean Austral communities. While most studies on plant responses to disturbances in the Pampean region have traditionally focused on specific plant functions (e.g., Candeias and Fraterrigo \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) or on specific environmental gradients (e.g., Garnier et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), our approach involved characterizing 17 traits across 140 species and analyzing how these traits are filtered by fire, grazing, and drought using field experiences. We assessed the functional response of the grasslands in the Austral Pampa using RLQ and Fourth-corner methods. Below, we present a list of functional traits that can be used to assess the health of grasslands and discuss the relative impact of each disturbance on plant community assembly.\u003c/p\u003e "},{"header":"Methods","content":" \u003cp\u003eStudy sites\u003c/p\u003e \u003cp\u003eWe recorded field characteristics in three areas of the Ventania mountains in the Pampean biogeographical province (Central Argentina). The climate of the study area is temperate, with an average annual temperature of 14\u0026deg; C and average precipitation of 800 mm, most of which falls in spring and fall, with occasional snow falls in winter (Michalijos \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The study area includes high plains (\u0026gt;\u0026thinsp;700 m.a.s.l.) composed of shallow rocky soils, piedmont grasslands and intermountain valleys both with consolidated soil (0.3 to 0.5 m depth) with superficial rocks (Long \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThree areas with intact grasslands were selected in a region that extends 150 km from south to north and 40 km from west to east (Guerrero and Apodaca \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The three areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were all selected because they include sites exposed to varying fire frequency, herbivory intensity and water stress during drought events: (a) the Ernesto Tornquist Provincial Park (ETPP) (38\u0026deg;03\u0026prime;00\u0026Prime;S 62\u0026deg;02\u0026prime;00\u0026Prime;W), a 6,700-ha-conservation area established in 1942 that contains the last relicts of Pampean grasslands in a relatively good state of conservation (Bilenca and Mi\u0026ntilde;aro 2004); (b) the protected natural area Sierras Grandes (SGAP) (38\u0026deg;10\u0026prime;14\u0026Prime;S 61\u0026deg;54\u0026prime;06\u0026Prime;W), a 2,300-ha-conservation area established in 2013; (c) the Ceferino Hill (320 m.a.s.l.) that has neighboring piedmont grasslands (CHNG) (38\u0026deg;07\u0026prime;36\u0026Prime;S 61\u0026deg;47\u0026prime;20\u0026Prime;W). The two first areas have canyons that can protect a highly diverse vegetation (Long \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) from strong winds, while the third area is composed of less rugged hills, exposed to drier and colder conditions (Cambarieri \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The three selected areas are similar in their geological and evolutionary history, making them comparable to each other (Demieri et al. 2005)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe most abundant plants species are perennial tussock grasses, such as \u003cem\u003eNasella\u003c/em\u003e and \u003cem\u003ePiptochaetium\u003c/em\u003e spp. and shrubs such as \u003cem\u003eDiscaria americana\u003c/em\u003e and \u003cem\u003eEupatorium buniifolium\u003c/em\u003e (Cabrera \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1976\u003c/span\u003e). The native herbivorous pampas deer (\u003cem\u003eOzotoceros bezoarticus\u003c/em\u003e) and guanaco (\u003cem\u003eLama guanicoe\u003c/em\u003e) that were highly abundant in the Pampean grasslands in the pre-hispanic period are now either extinct or persist but at extremely low densities (Bilenca and Mi\u0026ntilde;arro 2004). Over the course of the 18th century, these species were replaced by domestic livestock, cattle (\u003cem\u003eBos taurus\u003c/em\u003e) and horses (\u003cem\u003eEquus caballus\u003c/em\u003e) (Modernel et al.,2016). Today domestic livestock are present in the two first areas, mainly horses in ETPP and cattle in SGAP (Giunti and Long \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Scorolli \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), at a density higher than that recommended (0.15 UA) for Pampean Austral grasslands (Distel \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and are also present in the third area, but at lower densities. Fire frequency has been reported to have increased threefold compared to the historical record (Brancatelli et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) in the two first sites.\u003c/p\u003e \u003cp\u003eIn each area, we characterized the vegetation and species traits in eight sampling sites (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e): two grassy sites grazed by livestock, the first grazed mostly by cattle and the second mostly by horses, both without any occurrence of wildfires recorded for at least 20 years (Grazed: SG1 and SG2 respectively); two grassy sites subject to different fire frequencies, respectively every two years (SF1) and every four years (SF2), without domestic livestock grazing for at least 20 years; two drier grassy sites (located at higher altitudes), the first at 300 m above sea level (SD1) and the second at 400 m above sea level (SD2), both sites free from wildfires and domestic livestock grazing; and two grassy sites (as controls) in the vicinity of grazed sites but not grazed and where no fire has occurred in at least 20 years (SC1 and SC2) (Appendix S1). The distance between the study sites ranged from 5 to 25 km. Their topography and soil characteristics are described according to Demieri et al. (2005) and Kristensen and Frangi (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The soil depth of each sampling site was measured with a graduated soil auger. Temperature and precipitation data were obtained from the meteorological stations located closest to the experimental sites (INTA 2022) and their average annual values were calculated for the study period (2015\u0026ndash;2019).\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\u003eProperties and environmental characteristics of the study sites. Sampling sites: fire frequency, every two (SF1) and four years (SF2); drier conditions at 300 m.a.s.l. (SD1) and at 400 m.a.s.l. (SD2), and control sites not grazed or fire has occurred in at least 20 years (SC1 and SC2).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSampling\u003c/p\u003e \u003cp\u003esites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of disturbance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurface area\u003c/p\u003e \u003cp\u003e(hectares)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnnual precipitation (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean temperature\u003c/p\u003e \u003cp\u003e(\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoil depth\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSG1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHorses grazing\u003c/p\u003e \u003cp\u003e(0.35 LSU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e847.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eShallow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSG2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSGAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCattle grazing\u003c/p\u003e \u003cp\u003e(0.25 LSU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e935.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDeep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSF1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFires every two years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e850.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eShallow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSF2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSGAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFires every four years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e894.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDeep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSD1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDrought\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e708.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRocky\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSD2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDrought\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e652.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRocky\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDeep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSC2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e945.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDeep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLSU: livestock units per hectare.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThe annual average precipitation and temperature were calculated for the sampling period (2015\u0026ndash;2019).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSoil depth: Shallow (\u0026lt;\u0026thinsp;0.15 m deep); Deep (\u0026gt;\u0026thinsp;0.15 m deep); Rocky: rocks visible on the surface. The classification by soil depth ranges is according to Imbellone et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn each sampling site, we randomly distributed 20 plots (1 m2) and described their vegetation every spring and summer from 2015 to 2019. Each species was identified and its cover estimated using the Braun-Blanquet scale and the ordinal classes obtained were transformed into the average percentage covers of each class. We used for the analyses the average cover per species over the 5 years of sampling and species with less than 5% cover were not considered in the analyses (Krebs \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Species taxonomy and nomenclature were unified according to Zuloaga et al. (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSelection and characterization of functional traits\u003c/p\u003e \u003cp\u003eWe selected 17 categorical and numerical functional traits that provide information about the processes involved in the functional response of plant species to the conditions created by livestock grazing, frequent fires and drought (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most traits were measured both in the field and in the laboratory; some were completed by information already available in databases and in the literature. All quantitative traits were measured on 5 individuals per species, randomly selected at each experimental site according to the criteria and methodologies proposed by Perez Harguindeguy et al. (2013). Plant height was measured in the field as the vertical height of the longest stem, branch or clump with a ruler, considering the surface of the ground as zero. We collected 10 fruits from each species and counted the number of seeds per fruit. Ten seeds were then harvested per plant and their length was recorded using a digital caliper. If the seeds were very small, they were measured under a binocular microscope. We counted the number of green leaves per plant on the three tallest stems of 5 randomly selected individuals per species. We compared leaf areas using the product of the width and length of 10 leaves on 3 stems of 5 individuals of each species, measured with a digital caliper. The average leaf area was multiplied by the average number of leaves recorded.\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\u003eDescription of the traits. Variables are either continuous (C) or categorical (F); the description and category of the variables of each functional trait are reported as V for vegetative and G for generative.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFunctional role\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlant height\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVertical height (cm) of the longest stem, branch or clump measured from the surface of the ground\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u0026deg; of seeds\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of seeds per fruit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSize of seed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLength (cm) of at least 10 seeds per plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u0026deg; of leaves\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of leaves or blades of the tallest stems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFlower cluster\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(single flower\u0026thinsp;=\u0026thinsp;0; cluster of flowers\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup of flowers arranged on a stem composed of a main branch or a complicated arrangement of branches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerenniality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(annual or biannual\u0026thinsp;=\u0026thinsp;0; perennial\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvival for at least three growth cycles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePollination\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(entomophilous\u0026thinsp;=\u0026thinsp;0; anemophilous\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePollen dispersal by wind (anemophilous) or by insects (entomophilous)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDehiscence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(fruit indehiscent\u0026thinsp;=\u0026thinsp;0; fruit dehiscent\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFruits with mechanism that allows the spontaneous release of seeds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDormancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(no dormant seeds\u0026thinsp;=\u0026thinsp;0; dormant seeds\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeeds with any mechanism that prevents germination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnimal dispersal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(other dispersing agents\u0026thinsp;=\u0026thinsp;0); animal dispersal\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFruit dispersal by animals (exo and endozoochory)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpinescence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(without spines\u0026thinsp;=\u0026thinsp;0; with spines\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStem or leaf spines that hinder or prevent grazing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeaf hairiness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(without hair\u0026thinsp;=\u0026thinsp;0; with hair\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeaves and stems have prolonged epidermal cells (trichomas)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLateral exploration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(without stolons or rhizomes\u0026thinsp;=\u0026thinsp;0; with stolons or rhizomes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStolons and rhizomes that promote lateral exploration and vegetative propagation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStorage organs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(without underground stems\u0026thinsp;=\u0026thinsp;0; with underground stems\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTubers, corms, rhizomes, bulbs, and other belowground stems that help the plant survive for long periods of time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResprouting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(without capacity to resprouting\u0026thinsp;=\u0026thinsp;0; with capacity to resprouting\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCapacity to activate dormant vegetative buds to produce regrowth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eErect habit\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(no erect habit\u0026thinsp;=\u0026thinsp;0; erect habit\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith upright main stem(s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeaf area\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurface area of the leaves or blades (cm\u003csup\u003e2\u003c/sup\u003e) of the longest stems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe descriptions of functional traits are based on Perez Harguindeguy et al. (2013) and Wigley et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eWe analyzed the relationships between functional traits and environmental variables using the RLQ and fourth-corner analyses using the vegan package (Oksanen et al., 2013) and ade4 package (Dray et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) all in R (version 3.0.2, R Core Team 2022). RLQ analysis links a matrix of environmental variables per site (R) to a species/traits matrix (Q) using the species/sites matrix (L) as a link. We applied a Hellinger transformation to the species distribution matrix to reduce the influence of hyper-dominant species in our analyses, and both the environmental variables and traits matrices were standardized to remove variable dimensionality. Fourth-corner analysis made it possible to test the associations between functional traits and environmental variables, and RLQ analysis provided an ordination to evaluate the overall significance of the species-traits-environment relationships (Dray 2014).\u003c/p\u003e \u003cp\u003eDifferences in the numerical and categorical variables between groups of species with similar combinations of traits were analyzed by one-way analysis of variance for a completely randomized design (Zar \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Prior to the analysis of variance of the cardinal data, we made an approximation of the binomial distribution to the normal distribution using a Poisson goodness-of-fit test, and the numerical data were transformed to the square-root. The means were separated using the Tukey test (Zar \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The data were analyzed using Real Statistics Resource Pack software (Release 7.6) (Zaiontz, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe analyzed the relationships between plant traits and environmental variables in 140 plant species distributed in 31 families. The most represented families were Poaceae (21%) and Asteraceae (19%), followed by Fabaceae, Malvaceae and Caryophillaceae (5% each). This representation of families is comparable to that reported for the Pampa biome (Cabrera, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1976\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnvironmental factors related to past disturbances of the study areas had an impact on the function and structure of the plant communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Temperature, precipitation, frequency of fires and herbivory (total, by horses and by cattle) were positively or negatively correlated with at least one plant functional trait. Conversely, soil depth was not significantly correlated with any measured trait.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe found significant relationships for the plant trait/environmental factors using RLQ analysis. The first two RLQ axes explained 92.68% of the cumulative projected inertia (75.06% Axis 1 and 17.62% Axis 2). The first RLQ axis was positively correlated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with temperature and negatively correlated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with total cattle and horse herbivory and rainfall while the second axis was positively correlated with rainfall and soil depth and negatively correlated with temperature; fire frequency was not a strongly structuring environmental variable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and Appendix S3). Plant traits positively correlated with (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) the first axis were \u0026ldquo;perenniality\u0026rdquo; and \u0026ldquo;resprouting\u0026rdquo; while \u0026ldquo;leaf area\u0026rdquo; was negatively correlated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u0026ldquo;Anemophily\u0026rdquo;, \u0026ldquo;animal dispersal\u0026rdquo; and \u0026ldquo;erect habit\u0026rdquo; were positively correlated with the second axis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) while \u0026ldquo;leaf hairiness\u0026rdquo; and \u0026ldquo;spinescence\u0026rdquo; were negatively correlated with it (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and Appendix S4). No strong relationships with the environmental variables were found for the remaining nine traits in our analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe plant species were classified in functional groups based on their trait-environment scores in the RLQ analysis. The first two RLQ axes separated five ecologically differentiated functional groups (PFGs) of plants species with similar trait-environment responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The five PFGs differed significantly in an ANOVA based on their scores in the RLQ analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD): perenniality (F\u0026thinsp;=\u0026thinsp;10.4; p\u0026thinsp;=\u0026thinsp;6.2x10-09), type of pollination (F\u0026thinsp;=\u0026thinsp;9.8; p\u0026thinsp;=\u0026thinsp;10.5x10-08), resprouting capacity (F\u0026thinsp;=\u0026thinsp;7.4; p\u0026thinsp;=\u0026thinsp;0.0001), spinescence (F\u0026thinsp;=\u0026thinsp;5.7; p\u0026thinsp;=\u0026thinsp;0.0008), leaf hairiness (F\u0026thinsp;=\u0026thinsp;3.2; p\u0026thinsp;=\u0026thinsp;0.0221) and leaf area (cm2) (F\u0026thinsp;=\u0026thinsp;12.4; p\u0026thinsp;=\u0026thinsp;7.045x10-06). Seed dormancy and the number of seeds did not differ significantly between groups (ANOVA; F\u0026thinsp;=\u0026thinsp;0.40; p\u0026thinsp;=\u0026thinsp;0.8170 and F\u0026thinsp;=\u0026thinsp;1.90; p\u0026thinsp;=\u0026thinsp;0.1297 respectively).\u003c/p\u003e \u003cp\u003eThe five PFGs correspond to (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e):\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptions of the plant functional groups (PFG) identified. The number of species (S) in the group, the typical species and the dominant characters of each group are reported.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePFG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTypical species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDominant characters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAbutilon terminale, Baccharis artemisioides, B. articulata, Dichondra sericea, Lucilia acutifolia, Margyricarpus pinnatus, Mimosa rocae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSmall perennial plants (\u0026lt;\u0026thinsp;0.20 m tall), with small hairy leaves, stem and root have sprouting capability and dehiscent fruits with numerous small seeds\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAdesmia pampeana, Chaptalia integerrina, Eryngium nudicaule, Festuca pampeana, Gamochaeta filaginea, Helenium radianum, Holocheilus brasiliensis, Piptochaetium hackelii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePerennial, annual and biannual plants, with erect, rosette and prostrate growth, mostly short herbs and tussock grasses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eAristida spegazzini, Bromus catharticus, Daucus pusillus, Erodium cicutarium, Geranium molle, Hordeum geniculatum, Hypochaeris glabra, Poa ligularis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnnual or biannual plants (0.10\u0026ndash;0.30 m tall), with rosette or erect growth and medium to large soft leaves, anemophilous pollination and dormant seeds\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardus acanthoides, C. pycnocephalus, Echium plantagineum, E. vulgare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnnual or biannual plants, frequently rosettes and with spines on either leaves or stems. Mostly weeds and pioneer plants\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eChascolytrum brizoides, Koeleria ventanicola, Melica argyrea, Nasella neesiana, N. tenuis, Piptocaetium lejopodum, P. montevidense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTall perennial plants (0.20\u0026ndash;0.60 m tall), with erect growth and anemophilous pollination, mostly tussock perennial grasses\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 \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e PFG1 - Drought tolerators: short statured species with small hairy leaves and high resprouting capacity.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePFG2 - Generalists: species with intermediate trait values for all traits recorded and no clear functional specialization.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePFG3 - Drought intolerants: crawling annual species with large leaves growing in sites with deeper soils and high water availability.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePFG4 - Herbivore resistors and avoiders: either spiny species or species with a non-erect growth form (e.g., rosette or prostrate) that expose their leaves flat on the soil surface.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePFG5 Herbivore-susceptible: tall, erect, perennial species with anemophilous pollination and fruits dispersed by animals. This group presents mostly species belonging to the \"flechillar\" community (perennial tussock grasses), typical of pristine grasslands in the Pampean region.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of our analysis of the functional responses of 140 plant species using 17 functional traits, shows that the Austral Pampean grassland host communities function very differently. The communities respond differently to environmental factors that are currently impacted by global climate change and anthropogenic activities, which is creating novel climates and novel disturbance regimes. Drought and the herbivory regime were found to strongly influence plant communities in the Pampean region, in agreement with previous studies (Koerner and Collins \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ratajczak and Ladwig, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while changes in the historic fire record seemingly did not. Analyzing these factors together was important to be able to reveal their effects on the functional responses of Pampean communities. We now discuss how our findings provide the basis for more reliably predicting community responses to the consequences of climate change and anthropogenic activities, and how conservation and management practices could influence the emergence of unique community types in the Pampean biome.\u003c/p\u003e \u003cp\u003eDisturbances promote alternative functional groups in Pampean grasslands\u003c/p\u003e \u003cp\u003eWhile at first glance, Pampean grasslands may appear to be uniform as they share similar physiognomies, our analyses identified five functional groups of species with contrasted lifespans, pollination and dispersal, ability to resprout after disturbances, defenses, and drought adaptations on their leaves. Interestingly, the disturbance regime was important for the emergence of communities with distinct suites of trait and calls for conservation actions that manage the type, intensity and frequency of disturbance. Our control treatment, which corresponded to the exclusion of all disturbances, only promoted one of the five functional groups (PFG5) corresponding to perennial tussock grasses of the genera \u003cem\u003eNassella\u003c/em\u003e and \u003cem\u003ePiptochaetium\u003c/em\u003e. Maintaining the high diversity of the Pampean grassy ecosystems therefore requires understanding the effect of disturbances and incorporating them in conservation actions.\u003c/p\u003e \u003cp\u003eEffects of drought\u003c/p\u003e \u003cp\u003eThe most arid environments only enabled communities with small hairy leaves that produce numerous seeds germinating without dormancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Vegetation types with small hairy leaves are typically found in arid environments (Moles et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) as both traits help mitigate water losses during drought events (Seleiman et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Species adapted to drier environments usually produce numerous seeds (Lorts et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), to secure persistence of the species by an effective dispersal that has a bigger chance of reaching wetter micro habitats. The lack of seed dormancy is not necessarily an advantage in the face of drought. Dormancy commonly helps avoid harsh seasons (dry or cold) and delays germination until conditions are more favorable for growth (Bewley et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the case of Pampa grasslands, the lack of dormancy of the functional group that survives well in the dry environment could be explained by seasonality, as the seeds are released during the fall wet season (Michalijos \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and could be one consequence of producing many seeds for which activating dormancy mechanisms could incur high costs.\u003c/p\u003e \u003cp\u003eEffects of herbivory\u003c/p\u003e \u003cp\u003ePampean grasslands have been deeply modified by the presence of herbivores: the communities in sites exposed to herbivory are composed of a larger proportion of short annual species with spiny stalks or leaves and larger leaves. This distinct suite of traits encountered in areas exposed to mammalian herbivory is consistent with the results of previous works (e.g., Lavorel and Garnier, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Borchardt et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lezama et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Charles-Dominique et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; de Villalobos and Schwerdt \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our analysis showed the effect of herbivory on community filtering to be particularly strong and confirmed that the presence of mammalian herbivores alters the vertical structure of the grasslands, as livestock tends to prefer taller species (Celaya et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and that the replacement of native herbivores such as guanacos by livestock can lead to major changes in composition, which, in some areas, could favor biological invasions in the Pampa biome (Chaneton et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Loydi and Zalba, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; de Villalobos et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Interestingly, understanding the effect of the novel herbivory regime in Pampa grasslands requires not only studying the effects of the density of herbivores compared to before the Hispanic herbivory regime but also the type of herbivory. Our results show that grazing by horses and cattle promoted different plant communities. Horse-grazed grasslands contain more plants with larger leaf areas (notably rosettes), whereas cattle-grazed grasslands contain spiny communities. The different communities that emerge in horse \u003cem\u003eversus\u003c/em\u003e cattle grazed sites is probably related to the distinct preferences of the two herbivores. Horses tend to prefer perennial grasses with narrow leaves (Roger et al. 2014), thereby creating gaps that provide light for large leaf forbs and short statured woody species that require more light than grasses (Garnier et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The promotion of forbs in grassy ecosystems by horses in mountain grasslands of the Austral Pampas was also reported by de Villalobos and Schwerdt (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and by Davies et al. (2019) in the Midwest of North America. Conversely, cows are more sensitive to spines and tend to select non-spiny species with higher nutritional quality, typically with a lower carbon-to-nitrogen ratio (Celaya et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Pauler et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The presence of native plant species with functional profiles that enable both horse and cattle herbivory, is first puzzling as it questions which herbivores could have selected for the species composing these communities in the pre-Hispanic period, and second, suggests that conservation programs in the Pampean region should find the right balance of herbivory (in terms of both the density and type of herbivore) to maintain the diversity of communities.\u003c/p\u003e \u003cp\u003eReduced effect of fire\u003c/p\u003e \u003cp\u003eSurprisingly, fire frequency had little effect on filtering plant communities in our study sites. This suggests that all the functional groups of species in the Pampean grasslands we analyzed are resilient to fire, as even under high fire frequency, we did not observe a strong filtering effect, either at species or trait level. Concerning traits, only spinescence and seed dormancy (sub-significant) were associated with higher fire frequency, but not with other functional traits, such as resprouting capacity, which is commonly associated with fire-prone systems (Pausas et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Clarck et al. 2013). Although seed dormancy has been suggested to promote fitness of plants in fire driven systems (Pausas and Lamont \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) when dormancy is released by the fire generated heat and enable plants to exploit the post-fire environment with reduced competition (de Villalobos et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Tangney et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), spinescence is not \u003cem\u003eper se\u003c/em\u003e a fire adaptation. Spinescence is rarely expressed in fire-driven systems (Charles-Dominique et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) except in areas subjected to pyric herbivory, a disturbance regime in which both large mammalian herbivores are present and fires occur regularly, thereby promoting communities that are adapted to both disturbances (Fuhlendorf et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Archibald et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The fact spiny species are favored in frequently burned sites questions whether such a pyric herbivory regime could have driven Pampean communities in the past and calls for experimentation that combines the two types of disturbances to evaluate the effects of their combination. This would help design conservation programs adapted to the functioning of the Pampean flora. Alternatively, the absence of a clear functional profile of species in burnt sites could be related to species with higher levels of functional plasticity (not monitored in the present study) that, in turn, could promote persistence in areas with frequent fires (Simpson et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The response of species to fire and their ability to resprout in the Austral Pampean grasslands may be influenced by complex interactions with a variety of factors, including fire intensity, and historical disturbance patterns. Such factors could modulate the relationship between fire and functional traits in a non-linear or context-dependent manner (Stephan et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). No differences were found between communities developing in sites with low (4-y-fire return interval) and high fire frequencies (2-y-fire return interval). Despite the increased occurrence of fires based on historical records in the study sites, it is possible that either these changes are too recent induce a community shift or that these fire frequencies fall within the expected frequency range that selected for the Pampas grassland ecosystems (Paruelo et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Giorgi et al. 2020).\u003c/p\u003e \u003cp\u003eCombined effects of different factors\u003c/p\u003e \u003cp\u003eWhile our analysis did not consider interactions between factors, it is important to study simultaneously the main factors that could influence community dynamics and composition as it allows separating responses specific to a unique factor versus traits that could be promoted by varied alternative drivers. For example, our analysis showed that traits related to livestock grazing and drought conditions both favored plants with resprouting capacity and short life cycles. Several other studies showed traits similarly favoured by drought and grazing (Milchunas et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Blumenthal et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Irob et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e): for example, deciduous leaves or short life cycles allow species to escape both drought and herbivory in the Austral Pampean grasslands. Short lived plants could complete their lifecycle swiftly during the wet season (Blonder et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and efficient resource allocation could facilitate their regrowth and rapid reproduction after grazing (Hendrickson and Olson \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Blumenthal et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also found that structural drought tolerance and avoidance traits were predictors of herbivore resistance in semi-arid shortgrass steppe and mixed grasslands in North America. Furthermore, Irob et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that Namibian savannas with a higher proportion of herbivores were more resilient to drought. The co-occurrence of drought and herbivore adaptations could be related to the greater need of plants to defend themselves against herbivory when they grow in a more constraining environment where regrowth (and hence tolerance to damage caused by herbivory) is difficult (Grubb \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study emphasizes the significance of taking functional traits into consideration when investigating plant communities in the Pampa biome. Analyzing how these traits are influenced by environmental factors and disturbances led to a more comprehensive understanding of community functioning and responses to environmental changes. This knowledge is critical to develop effective conservation and management strategies to preserve biodiversity and ecological integrity in the Pampa biome. Additionally, our findings provide insights into the dynamics of plant communities over time and their responses to environmental disturbances in the Austral Pampean grasslands. By examining the relationships among functional traits, environmental factors, and disturbances, we can conclude that the grasslands of the Austral Pampean region possess adaptive capacity to variations in disturbances, as evidenced by a diverse array of species with functional traits. These findings pave the way for more sustainable management and call for further studies aimed at promoting the long-term resilience and stability of the Austral Pampean grasslands.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.E.V. designed the field experiment and collected the data. T. C.-D. developed the statistical analysis methods. Both authors analyzed the data, wrote the manuscript and contributed critically to the drafts and gave final approval for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was funded by CONICET (Consejo Nacional de Investigaciones Cient\u0026iacute;ficas y T\u0026eacute;cnicas) and SGCyT, (Secretar\u0026iacute;a General de Ciencia y Tecnolog\u0026iacute;a, Universidad Nacional del Sur, Argentina). We wish to thank the administrations of Ernesto Tornquist Provincial Park and Sierras Grandes Protected Area, Provincia de Buenos Aires, as well as the Instituto Nacional de Tecnolog\u0026iacute;a Agropecuaria (INTA) Argentina. We are especially grateful to Andrea Long for her assistance in plant species determinations, and to Daphne Goodfellow for the English revision.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArchibald S, Hempson G P, Lehmann C (2019) A unified framework for plant life-history strategies shaped by fire and herbivory. 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Darwiniana Nueva Ser 7: 208\u0026ndash;278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14522/darwiniana.2019.72.861\u003c/span\u003e\u003cspan address=\"10.14522/darwiniana.2019.72.861\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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 traits, Herbs, Fire, Grazing, Drought, Pampa Austral, Natural grasslands, Open ecosystems.","lastPublishedDoi":"10.21203/rs.3.rs-4018818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4018818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Austral Pampa hosts extensive and diverse grasslands, which, over the last century, have been exposed to climate change and unprecedented disturbance regimes, including domestic herbivory and a novel fire regime. Predicting community responses to these changing conditions and designing appropriate conservation plans requires dissociating the individual contribution of each factor to community filtering. We ask whether fire, herbivory, temperature and drought, favor distinct communities in Pampean grassy ecosystems and which plant traits. Field surveys were conducted in three areas of the Ventania Mountain System in Pampa Austral (Argentina) exposed to varied fire, herbivory, and drought regimes. A total of 140 plant species were examined across 8 sampling areas, selected as representing different disturbance regimes. We measured 17 functional traits related to plant height, reproduction, and leaf area. The relationships between these traits and environmental variables were analyzed using RLQ and fourth-corner methods. RLQ analysis revealed that temperature, rainfall, and herbivory influenced plant communities, while fire frequency had less impact. We identified five distinct plant functional groups (PFGs) that differed in perenniality, type of pollination, resprouting capacity, spinescence, leaf hairiness and leaf area. Separating the effects of herbivory, fire, and drought reveals that multiple stresses could influence communities, resulting in higher resprouting and shorter life cycles. Analyzing how functional traits respond to environmental factors and disturbances provides insights into the conservation challenges posed by these changing disturbance dynamics in the Pampa biome.\u003c/p\u003e","manuscriptTitle":"Disturbance regimes favor alternative plant communities in the natural grasslands of the Pampa Austral (Argentina)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 18:44:39","doi":"10.21203/rs.3.rs-4018818/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-29T21:29:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T21:07:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"144143530309585097018420337754993324591","date":"2025-07-29T15:26:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152449495490358575552164286121592431515","date":"2025-07-25T20:51:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55488311091870614397571719776430261024","date":"2025-07-24T12:51:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141497627244182268234311087645603079399","date":"2025-07-23T16:28:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39285193300802214809637359943446081702","date":"2025-07-22T20:16:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-10T17:59:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292967863287124436054925851206384666143","date":"2025-06-25T05:17:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231158908953292034272356347948990049153","date":"2025-06-23T20:40:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-18T06:12:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-07T22:42:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-06T00:28:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Ecology","date":"2024-03-05T23:47:02+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":"b4bac9f3-da3d-4776-99d5-44a7c16e4c3f","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-15T15:59:07+00:00","versionOfRecord":{"articleIdentity":"rs-4018818","link":"https://doi.org/10.1007/s11258-025-01565-3","journal":{"identity":"plant-ecology","isVorOnly":false,"title":"Plant Ecology"},"publishedOn":"2025-09-10 15:57:11","publishedOnDateReadable":"September 10th, 2025"},"versionCreatedAt":"2024-03-11 18:44:39","video":"","vorDoi":"10.1007/s11258-025-01565-3","vorDoiUrl":"https://doi.org/10.1007/s11258-025-01565-3","workflowStages":[]},"version":"v1","identity":"rs-4018818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4018818","identity":"rs-4018818","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}