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Belowground differentiation among trees in a degraded tropical dry forest landscape: no evidence of a collaboration gradient

Published online by Cambridge University Press:  27 May 2024

Juan Pablo Benavides-Tocarruncho
Affiliation:
Departamento de Biología, Universidad Nacional de Colombia, Bogotá, Colombia
Horacio Paz
Affiliation:
Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, Mexico
Nelly Rodríguez
Affiliation:
Departamento de Biología, Universidad Nacional de Colombia, Bogotá, Colombia
Rosa Arrieta
Affiliation:
Departamento de Biología, Universidad Nacional de Colombia, Bogotá, Colombia
Camila Pizano
Affiliation:
Departamento de Biología, Universidad Icesi, Cali, Colombia Department of Biology, Lake Forest College, Lake Forest, IL, USA
Beatriz Salgado-Negret*
Affiliation:
Departamento de Biología, Universidad Nacional de Colombia, Bogotá, Colombia
*
Corresponding author: Beatriz Salgado-Negret; Email: [email protected]
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Abstract

Fine roots are specialized in nutrient and water acquisition and are critical for species performance and ecosystem functioning. Recent evidence has shown a broad root economic space determined by the orthogonal collaboration and conservation gradients related to resource acquisition and resource conservation, respectively. However, whether these gradients exist among tree species growing in degraded ecosystems where root growth is limited by soil conditions is much an open question. We measured six fine root traits (root diameter, specific root length, root dry matter content, root tissue density, branching intensity, and percentage of arbuscular mycorrhizal colonization) in 11 young tree species growing in sympatry for 9 years in degraded pastures in a tropical dry forest (TDF) in Colombia to determine (1) the covariation between fine root traits and (2) the patterns of belowground niche differentiation among 11 species coexisting under the same soil conditions. The covariation between fine root traits resembled the acquisitive-conservative, but not the collaboration gradient for this degraded habitat. The percentage of mycorrhizal colonization, a critical trait associated with the collaboration gradient, was unrelated to any fine root trait. Furthermore, we found a strong belowground differentiation among species, mainly across root diameter and branching intensity. Our results suggest that compacted degraded soils in TDF landscapes may affect the collaborative association with mycorrhizae, mostly allowing species differentiation along the do-it-yourself gradient. This finding suggests a hypothesis that needs to be tested with more species and sites. We discuss the importance of using root traits to aid species selection for restoration purposes.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Introduction

Soil and vegetation cover degradation resulting from anthropogenic practices such as cattle, agriculture, and urbanization have impacted the dynamics and functioning of forests worldwide (Jie et al. Reference Jie, Jing-Zhang, Man-Zhi and Zi-Tong2002). Land degradation has been extreme in tropical dry forests (TDF), which used to represent 42% of all the world’s tropical forests (Brown & Lugo Reference Brown and Lugo1982), with more than 50% left in South America (Miles et al. Reference Miles, Newton, Defries, Ravilious, May, Blyth, Kapos and Gordon2006). In Colombia, around 90% of its cover was replaced by the end of the 20th century (Etter et al. Reference Etter, McAlpine and Possingham2008; García et al. Reference García, Corzo, Isaacs, Etter, Pizano and García Martínez2014), and only 8% of TDF’s original cover is left in land mosaics of early successional stages (González-M et al. Reference González-M, Garcia, Isaacs, Cuadros, López-Camacho, Rodriguez, Pérez, Mijares, Castano-Naranjo, Jurado, Idárraga-Piedrahita, Rojas, Vergara and Pizano2018). In these degraded landscapes, natural regeneration is challenging, and planting trees is necessary for re-establishing local biodiversity and ecosystem functioning (Rodrigues et al. Reference Rodrigues, Lima, Gandolfi and Nave2009; Garbowski et al. Reference Garbowski, Avera, Bertram, Courkamp, Gray, Hein, Lawrence, McIntosh, McClelland, Post, Slette, Winkler and Brown2020; Werden et al. Reference Werden, Zarges, Holl, Oliver, Oviedo-Brenes, Rosales and Zahawi2022). However, water limitation imposed by the pronounced dry season (3–6 dry months precipitation <100 mm⋅month−1, Portillo-Quintero and Sánchez-Azofeifa, Reference Portillo-Quintero and Sánchez-Azofeifa2010; González-M. et al. Reference González-M, Norden, Posada, Pizano, García, Idárraga-Piedrahita, López-Camacho, Nieto, Rodríguez-M, Torres, Castaño-Naranjo, Jurado, Franke-Ante, Galindo-T, Hernández R, Barbosa and Salgado-Negret2019), which is exacerbated by soil compaction due to livestock grazing (Batey Reference Batey2009; Tracy et al. Reference Tracy, Black, Roberts and Mooney2011), represents a barrier to the successful restoration of degraded TDF. Under this scenario, exploring the variation and coordination of belowground traits among species will be fundamental for selecting species that can overcome the soil barriers dominant in dry degraded ecosystems.

Fine roots, which are the most distal orders of fine root systems (typically first- to third-order roots), are specialized in nutrient and water acquisition (McCormack et al. Reference McCormack, Dickie, Eissenstat, Fahey, Fernandez, Guo, Helmisaari, Hobbie, Iversen, Jackson, Leppälammi-Kujansuu, Norby, Phillips, Pregitzer, Pritchard, Rewald and Zadworny2015) and therefore critical for species performance in degraded ecosystems (Paz et al. Reference Paz, Pineda-García and Pinzón-Pérez2015; Garbowski et al. Reference Garbowski, Avera, Bertram, Courkamp, Gray, Hein, Lawrence, McIntosh, McClelland, Post, Slette, Winkler and Brown2020; Werden et al. Reference Werden, Zarges, Holl, Oliver, Oviedo-Brenes, Rosales and Zahawi2022). Recent studies have identified two main functional belowground gradients expressing globally (Bergmann et al. Reference Bergmann, Weigelt, van der Plas, Laughlin, Kuyper, Guerrero-Ramirez, Valverde-Barrantes, Bruelheide, Fresche, Iversen, Kattge, McCormack, Meier, Rillig, Roumet, Semchenko, Sweeney, van Ruijven, York and Mommer2020). One gradient encompasses plants that optimize resource uptake by investing carbon in thin roots that efficiently explore the soil themselves (“do-it-yourself”) to those that “outsource” resource acquisition via mycorrhizal associations, whereby an expanded cortical area of roots provides a wider intraradical habitat for their fungal partners (Raven & Edwards Reference Raven and Edwards2001; Brundrett Reference Brundrett2002; Kong et al. Reference Kong, Ma, Zhang, Li, Chen, Zeng and Guo2014; Ma et al. Reference Ma, Guo, Xu, Lu, Bardgett, Eissenstat, McCormack and Hedin2018; Brundrett & Tedersoo Reference Brundrett and Tedersoo2018). The acquisition-conservation gradient, orthogonal to the collaboration gradient, represents a trade-off between traits linked to high metabolic activity (e.g., root nitrogen) and those associated with the costs of root construction (e.g., root tissue density [RTD] or root dry matter content [RDMC]) (McCormack & Iversen Reference McCormack and Iversen2019; Bergmann et al. Reference Bergmann, Weigelt, van der Plas, Laughlin, Kuyper, Guerrero-Ramirez, Valverde-Barrantes, Bruelheide, Fresche, Iversen, Kattge, McCormack, Meier, Rillig, Roumet, Semchenko, Sweeney, van Ruijven, York and Mommer2020). These gradients have been reported across natural ecosystems worldwide (Bergmann et al. Reference Bergmann, Weigelt, van der Plas, Laughlin, Kuyper, Guerrero-Ramirez, Valverde-Barrantes, Bruelheide, Fresche, Iversen, Kattge, McCormack, Meier, Rillig, Roumet, Semchenko, Sweeney, van Ruijven, York and Mommer2020). However, the exploration of root traits covariation and its importance for the belowground niche partitioning among species is infrequently studied in degraded habitats. For example, the dry compacted soils typical of degraded TDFs may affect root exploration capabilities (Alameda & Villar Reference Alameda and Villar2012), their morphology, and root partnership with mycorrhizae as they are mostly involved in P but not in water acquisition (Smith & Read Reference Smith and Read2009). These factors may limit belowground niche partitioning along the collaborative more than across the conservative gradient as water acquisition may critically depend on root morphology and mass deployment.

In the present study, we used six fine root traits (root diameter [D], specific root length [SRL], RDMC, RTD, branching intensity [BI], and percentage of arbuscular mycorrhizal colonization [%M]) measured in young individuals of 11 TDF tree species growing in sympatry for 9 years in a degraded TDF landscape. Our aims were (1) to define covariation between fine root traits and (2) to explore the belowground niche partitioning among 11 species coexisting under the same compacted soil conditions.

Methods

Study site and species

The study area is located in the restoration area of El Quimbo in the department of Huila, Colombia (75°41’ W, 2°18’ N), between 700 and 800 m of altitude. The zone is classified as a TDF with a mean annual temperature of 24°C and an annual mean precipitation of 1036 mm in a bimodal regime, with dry seasons from June to August and from December to January (Avella-M. et al. Reference Avella-M, García-G, Fajardo-Gutiérrez, González-Melo, Avella-M, García-G, Fajardo-Gutiérrez and González-Melo2019). We took advantage of a restoration experiment established 9 years ago in abandoned pasture lands in which 11 common tree species (Table 1) were transplanted to plots containing individuals of all species randomly distributed, thus controlling for individual age and soil conditions (Torres-Rodríguez et al. Reference Torres-Rodríguez, Díaz-Triana, Villota, Gómez and Avella-M2019). Soil bulk density varies between 0.8 and 1.2 (1.1 on average; unpubl. data) grams per cm3, slopes vary between 0.1° and 14°, and the soils are classified as inceptisols and mollisols with low P, K, and organic matter content due to cattle ranching (Torres-Rodríguez et al. Reference Torres-Rodríguez, Díaz-Triana, Villota, Gómez and Avella-M2019).

Table 1. Tree species studied in a tropical dry forest in Huila, Colombia. Family, common name, code, leaf habitat, and wood density (WD) per species. Range (min-max) and mean (in parenthesis) for height (H) and diameter at breast height (DBH) of trees sampled per species. *Wood density was obtained from Gonzalez et al. (Reference González-M, Posada, Carmona, Garzón, Salinas, Idárraga-Piedrahita, Pizano, Avella, López-Camacho, Norden, Nieto, Medina, Rodríguez-M, Franke-Ante, Torres, Jurado, Cuadros, Castaño-Naranjo, García and Salgado-Negret2021)

Functional traits

Five individuals of each species were sampled in 2021, nine years after they were planted as saplings. Individual height varied between 1.7 m (Casearia corymbosa) and 6 m (Guazuma ulmifolia and Celtis iguanaea). For each individual tree, fine roots were sampled by following lateral roots growing radially from the main shoot until fine roots (2 mm or less in thickness) were found. Then, following the order-based classification (McCormack et al. Reference McCormack, Dickie, Eissenstat, Fahey, Fernandez, Guo, Helmisaari, Hobbie, Iversen, Jackson, Leppälammi-Kujansuu, Norby, Phillips, Pregitzer, Pritchard, Rewald and Zadworny2015), the fine roots were separated into individual root orders, prioritizing the collection of the first three orders. The diameter of our fine roots ranged from 0.25 to 0.71 mm (Table S1). The fresh weight of the sampled roots for each individual varied between 0.8 and 1.0 g.

In the field, fine roots were carefully collected, washed, and stored in plastic bags filled with water inside a cooler for transportation to the field station laboratory. Upon arrival at the laboratory, the fresh roots were cleaned, weighed, and scanned at 300 dpi (Epson Perfection V700 Photo scanner). Then, the roots were dried in an oven at 70°C for 48 hours and weighed to estimate the dry weight. The images were analyzed with RhizoVision Explorer, an open-source software for root trait measurement (Seethepalli et al. Reference Seethepalli, Dhakal, Griffiths, Guo, Freschet and York2021). We obtained six morphological traits (Table 2) using the weights and the measurements from the scanned roots: (1) average root diameter (D, mm) computed as the mean of all diameters in each skeleton pixel, (2) Specific root length (SRL, m g−1) calculated by dividing total length by the dry weight, (3) root dry matter content (RDMC, mg g 1) calculated by dividing the dry weight by the fresh weight, and (4) root tissue density (RTD, g cm−3) calculated by dividing the dry weight by root volume, assuming root tissues to be cylindrical in shape (Freschet et al. Reference Freschet, Pagès, Iversen, Comas, Rewald, Roumet, Klimešová, Zadworny, Poorter, Postma, Adams, Bagniewska-Zadworna, Bengough, Blancaflor, Brunner, Cornelissen, Garnier, Gessler, Hobbie, Meier, Mommer, Picon-Cochard, Rose, Ryser, Scherer-Lorenzen, Soudzilovskaia, Stokes, Sun, Valverde-Barrantes, Weemstra, Weigelt, Wurzburger, York, Batterman, Gomes de Moraes, Janeček, Lambers, Salmon, Tharayil and McCormack2021). (5) Branching intensity (BI, mm−1)  was calculated as the total number of root branching points (“links,” where a lateral root is linked to its parent root) divided by the total length (Eissenstat et al. Reference Eissenstat, Kucharski, Zadworny, Adams and Koide2015; Seethepalli et al. Reference Seethepalli, Dhakal, Griffiths, Guo, Freschet and York2021). (6) The percentage of arbuscular mycorrhizal colonization (%M) was calculated by clearing fine roots with 3% KOH and 3% H2O2 acidified with 3% HCl, washed with distilled water and stained with 0.05% aniline blue in lactoglycerol solution (Zangaro et al. Reference Zangaro, Bononi and Trufen2000). Stained root segments of each harvested plant were then mounted on a slide, and the presence/absence of Arbuscular mycorrhizal fungi (AMF) was recorded at 100 intersect points for each slide (McGonigle et al. Reference McGonigle, Miller, Evans, Fairchild and Swan1990). Although RDMC and D are claimed to be tightly correlated with each other and with SRL, we decided to include all of them because for the TDF, these relationships remain unclear. There, species with high SRL have been reported to exhibit either high diameter but succulent low tissue density or the opposite (Sanaphre-Villanueva et al. Reference Sanaphre-Villanueva, Pineda-García, Dáttilo, Pinzón-Pérez, Ricaño-Rocha and Paz2022).

Table 2. Functional traits measured and their functional significance

Data analysis

To explore the patterns of covariation among fine root traits (first aim), we performed Pearson correlation with Bonferroni correction using the R Stats package (R Core Team 2021). To explore the belowground niche partitioning among 11 species (second aim), we followed 2 approaches (univariate and multivariate) using trait probability density (TPD) (Carmona et al. Reference Carmona, de Bello, Mason and Lepš2016). The TPD approach is based on estimating Gaussian kernel density functions around each observation (Carmona et al. Reference Carmona, de Bello, Mason and Lepš2016, Reference Carmona, de Bello, Mason and Lep S2019). The TPD function of a given species represents the probability of observing different trait values in that species considering all sampled individuals (Carmona et al. Reference Carmona, de Bello, Mason and Lepš2016). For the multivariate approach, we first generated a multivariate functional space among species by applying a Principal Component Analysis (PCA) on all plants measured per species and selecting the first two PCA axes as suggested by the Horn’s test for our data (Horn Reference Horn1965; Dinno Reference Dinno2018). Then taking the scores of each plant of every species along the first and second PCA axes, we calculated the multivariate functional niche of each species by using the TPD (Carmona et al. Reference Carmona, de Bello, Mason and Lepš2016), implemented in the TPD’s function of the R package “TPD” (Carmona et al. Reference Carmona, de Bello, Mason and Lep S2019). To explore belowground niche partitioning among species, we used the dissimilarity index (dissim function provided by the TPD package and TPD dissimilarity <0.05; Carmona et al. Reference Carmona, de Bello, Mason and Lep S2019) that measures the overlapping probability in the functional space between two species (TPD distributions). In addition, to better understand which functional traits differed most between species (univariate approach), we calculated functional niches based on single traits and compared them, following the same procedures described above. All statistical analyses were performed using R statistical software (R Core Team 2021).

Results

We found a negative correlation between root diameter (D) and all root traits except for %M which was not significantly correlated with D (Figure 1, Table S2). Additionally, we found a positive correlation between traits associated with construction root costs, RTD or RDMC, and BI (Figure 1, Table S2).

Figure 1. Pearson correlation coefficients with Bonferroni correction for pairwise relationships among six fine root traits. Significant correlations are indicated as red (negative) and blue (positive) ovals. Trait abbreviations: D: root diameter, %M: mycorrhizal colonization, RDMC: root dry matter content, RTD: root tissue density, BI: branching intensity, SRL: specific root length.

The bivariate relationships between traits were supported by the multivariate approach (Figure 2). The belowground trait space of the 11 tree species was summarized by the first 2 dimensions of the PCA (Figure 2a, Table S3), which together explained 73.3% of the among-individuals variation and were the only 2 significant components according to Horn’s test (Horn’s test adjusted eigenvalues greater than 1: 2.657 and 1.004, respectively). The first PCA axis (PC1 explaining 52.5%) suggested a trade-off between high BI and SRL (loading positively on PC1) and a high D (loading negatively on PC1). The contribution of %M to the first axis was low (Figure 2a, Table S3). The second PCA axis (PC2 explaining 20.8%) separated species with high tissue densities (i.e., high values of RTD and RDMC) located on the negative side from species with high SRL on the positive side (Figure 2a). However, it is important to note that both SRL and tissue density also partially contributed to PC1. The multivariate approach showed strong belowground niche partitioning among species, mainly across the D and BI gradient (PC1) (Figure 2b, Table S4). Species such as Celtis iguanaea (Ce.ig), Casearia corymbosa (Ca.co), and Guazuma ulmifolia (Gu.ul) with high scores on PC1 were significantly different from species with high values of D, such as Ceiba pentandra (Ce.pe), Tabebuia rosea (Ta.ro), Chloroleucon mangense (Ch.ma), and Ochroma pyramidale (Oc.py) (Figure 2b). We did not find differences between trees of different species along the PC2 (Figure 2b, Table S4).

Figure 2. Multivariate trait analysis. (a) PCA of six fine root traits. Each point in the PCA is an individual of a given species; color codes are shown in panel (b). Trait abbreviations: D: root diameter, BI: branching intensity, SRL: specific root length, RDMC: root dry matter content, RTD: root tissue density, %M: mycorrhizal colonization. (b) Trait probability densities (TPD) showing the functional trait combinations for eleven tree species. Species abbreviations are in Table 1; each species has a distinctive color in the PCA and TPD plots. Different letters in parenthesis next to the species abbreviation indicate significant differences between species using the dissimilarity index (>95% non-shared probability).

The multivariate divergences for the individual traits among species were supported by the univariate approach (Figure 3, Table S5S10). The species differentiation was mainly explained by D, with Ca.co and Ce.ig showing the thinnest roots and differing significantly from the other species (except Gu.ul and Pse.sep) (Figure 3a). Regarding BI, Ca.co showed the highest values and were statistically different from the other species (except for Ce.ig, Sapindus Saponaria (Sa.sa) and Gu.ul and Jacaranda caucana (Ja.ca) (Figure 3b). Ta.ro showed the lowest BI values and varied from Sa.sa, Ce.ig, and Ca.co, which had the highest values (Figure 3b). Concerning SRL, Ca.co showed the highest values and significantly differed from Oc.py, Ce.pe, Ch.ma, Ja.ca, and Machaerium capote (Ma.ca) (Figure 3c). We detected little differentiation among species for RDMC, RTD, and %M, probably associated with strong functional intraspecific variability (Figure 3d–f, Table S8S10).

Figure 3. Trait probability density for each of the 6 fine root traits and for the 11 tree species. The Y axis is the density. Trait abbreviations: D: root diameter, BI: branching intensity, SRL: specific root length, RDMC: root dry matter content, RTD: root tissue density, %M: mycorrhizal colonization. Species abbreviations are in Table 1. Different letters in parenthesis next to species abbreviations indicate significant differences between species according to the similarity index.

Discussion

Using 6 fine root traits measured in young individuals of 11 TDF tree species growing in degraded pastures in Colombia, we found ample variation in root traits that does not resemble the expectations from the collaboration gradient. The percentage of mycorrhizal colonization, an essential trait associated with the collaboration gradient, was unrelated to any fine root trait. Furthermore, we found strong species’ belowground differentiation mainly determined by the gradient between D versus BI and SRL rather than the acquisitive-conservative gradient. The differences in belowground niche among species highlighted their multiple strategies to deal with drought and penetrate compacted soils, essential information to understand species’ responses to climate change and to prioritize species for restoration purposes.

In principle, D and %M are expected to be tightly associated due to the limited intrinsic ability to acquire soil resources of thick roots (Bates & Lynch Reference Bates and Lynch2001); however, in our study, such traits varied independently. The lack of such correlation is not exclusive to our study, though no clear explanations have been claimed (Siqueira & Saggin-Júnior Reference Siqueira and Saggin-Júnior2001; Lugli et al. Reference Lugli, Andersen, Aragão, Cordeiro, Cunha, Fuchslueger, Meir, Mercado, Oblitas, Quesada, Rosa, Schaap, Valverde-Barrantes and Hartley2020). One possibility is that under habitats with dry soils, since mycorrhizal association enhances mainly P capture but not water (Gavito et al. Reference Gavito, Pérez-Castillo, González-Monterrubio, Vieyra-Hernández and Martínez-Trujillo2008; Smith & Read Reference Smith and Read2009, but see Bahadur et al. Reference Bahadur, Batool, Nasir, Jiang, Mingsen, Zhang, Pan, Liu and Feng2019), the root’s abilities to forage water may be more dependent on root morphology itself than on microbial associations. Alternatively, under low phosphorous availability, typical from old and weathered tropical soils (Vitousek Reference Vitousek2004), even finely branched roots may not ensure sufficient nutrient uptake by themselves, making them very responsive to and dependent on AMF (Siqueira & Saggin-Júnior Reference Siqueira and Saggin-Júnior2001). For instance, in our study, the species with the thinnest roots (Celtis iguanaea and Casearia corymbosa) exhibited mycorrhizal colonization percentages exceeding 42% on average. It is essential to recognize that the informative value of %M may be reduced, and identifying specific fungal groups through molecular techniques that better capture the functional nature of the symbiosis is needed (Cusack et al. Reference Cusack, Addo-Danso, Agee, Andersen, Arnaud, Batterman, Brearley, Ciochina, Cordeiro, Dallstream, Diaz-Toribio, Dietterich, Fisher, Fleischer, Fortunel, Fuchslueger, Guerrero-Ramírez, Kotowska, Lugli, Marín, McCulloch, Maeght, Metcalfe, Norby, Oliveira, Powers, Reichert, Smith, Smith-Martin, Soper, Toro, Umaña, Valverde-Barrantes, Weemstra, Werden, Wong, Wright, Wright and Yaffar2021). As we did not report a positive relationship between D and %M and, therefore, did not find a collaboration gradient, the negative relationship between D and SRL may reflect a mathematical autocorrelation more than ecological meaning (Ostonen et al. Reference Ostonen, Püttsepp, Biel, Alberton, Bakker, Lõhmus, Majdi, Metcalfe, Olsthoorn, Pronk, Vanguelova, Weih and Brunner2007). However, in TDFs, the previous observations of species with high SRL and high root diameters with low-density succulent tissues (Sanaphre-Villanueva et al. Reference Sanaphre-Villanueva, Pineda-García, Dáttilo, Pinzón-Pérez, Ricaño-Rocha and Paz2022) call for a functional role of both traits that still need to be studied in depth. Given the importance of mycorrhizal symbiosis for promoting the survival and growth of trees and shrubs within restoration experiments (Asmelash et al. Reference Asmelash, Bekele and Belay2019), an in-depth exploration of their role under degraded and dry soils becomes imperative.

The second gradient was related to resource acquisition-conservation, supported by a high RTD and RDMC (although we did not measure root N concentration). These results are consistent with other studies (Bergmann et al. Reference Bergmann, Weigelt, van der Plas, Laughlin, Kuyper, Guerrero-Ramirez, Valverde-Barrantes, Bruelheide, Fresche, Iversen, Kattge, McCormack, Meier, Rillig, Roumet, Semchenko, Sweeney, van Ruijven, York and Mommer2020; Arrieta-González et al. Reference Arrieta-González, Paez, Dominguez-Haydar and Salgado-Negret2021; Weemstra et al. Reference Weemstra, Valverde-Barrantes, Fortunel, Oblitas Mendoza, Prata, Vásquez Pilco, Vicentini, Vleminckx and Baraloto2023). Surprisingly, conservative traits such as RTD and RDMC were negatively related to D (Werden et al. Reference Werden, Zarges, Holl, Oliver, Oviedo-Brenes, Rosales and Zahawi2022), challenging the traditional idea that D increases with RTD for carbon conservation (McCormack et al. Reference McCormack, Adams, Smithwick and Eissenstat2012; Weemstra et al. Reference Weemstra, Mommer, Visser, Van Ruijven, Kuyper, Mohren and Sterck2016). This negative correlation may reflect that D increases through the root cortex, a parenchymatous tissue with low carbon content and dry weight, faster than the stele area, a tissue specialized in transporting nutrients and water through lignified cells (Kong et al. Reference Kong, Ma, Zhang, Li, Chen, Zeng and Guo2014; Valverde-Barrantes et al. Reference Valverde-Barrantes, Freschet, Roumet and Blackwood2017). The common observation of thick roots with low tissue density in other TDFs suggests a potential role of water storage in fat roots in maintaining tissue hydration within a dry soil matrix (Paz et al. Reference Paz, Pineda-García and Pinzón-Pérez2015; Sanaphre-Villanueva et al. Reference Sanaphre-Villanueva, Pineda-García, Dáttilo, Pinzón-Pérez, Ricaño-Rocha and Paz2022). Interestingly, according to the PCA, in our study, SRL was an important trait contributing to both root gradients, which has already been reported by other studies (Cusack et al. Reference Cusack, Addo-Danso, Agee, Andersen, Arnaud, Batterman, Brearley, Ciochina, Cordeiro, Dallstream, Diaz-Toribio, Dietterich, Fisher, Fleischer, Fortunel, Fuchslueger, Guerrero-Ramírez, Kotowska, Lugli, Marín, McCulloch, Maeght, Metcalfe, Norby, Oliveira, Powers, Reichert, Smith, Smith-Martin, Soper, Toro, Umaña, Valverde-Barrantes, Weemstra, Werden, Wong, Wright, Wright and Yaffar2021; Weemstra et al. Reference Weemstra, Valverde-Barrantes, Fortunel, Oblitas Mendoza, Prata, Vásquez Pilco, Vicentini, Vleminckx and Baraloto2023; but only in pairwise correlations in Bergmann et al. Reference Bergmann, Weigelt, van der Plas, Laughlin, Kuyper, Guerrero-Ramirez, Valverde-Barrantes, Bruelheide, Fresche, Iversen, Kattge, McCormack, Meier, Rillig, Roumet, Semchenko, Sweeney, van Ruijven, York and Mommer2020). The longer and thinner fine roots can increase overall absorptive capacity (“do-it-yourself” strategy), but the negative correlation with conservative traits could be explained mathematically (as long as the volume is filled with dry mass and not water or air), as high RTD implies more root mass per unit root volume and generally decreases the root mass per unit root length (Weemstra et al. Reference Weemstra, Valverde-Barrantes, Fortunel, Oblitas Mendoza, Prata, Vásquez Pilco, Vicentini, Vleminckx and Baraloto2023).

Although our species were planted in a pasture with similar soils and drought conditions, we found strong belowground differentiation among species mainly through the D-BI gradient rather than the acquisitive-conservative gradient. The compacted soils, typical of degraded pastures in dry ecosystems, could promote strong differentiation in traits associated with resource acquisition strategies (D vs BI and SRL). Under compacted soils, cortical cells tend to become broader and shorter as a strategy to penetrate soils, protecting the stele and causing thicker roots (Atwell Reference Atwell1993). Conversely, mechanical damage caused by soil compaction may also alter the root system architecture in some species, forcing lateral roots to alter their direction of growth and resulting in an increase in lateral root branching (Chen et al. Reference Chen, Palta, Clements, Buirchell, Siddique and Rengel2014), which is particularly important in those species unable to develop thick roots. Additionally, thick roots have higher storage space for accumulating water and starch (cortical cells, Lux et al. Reference Lux, Luxová, Abe and Morita2004); both resources are fundamental for drought responses under stomatal closure (Sala et al. Reference Sala, Piper and Hoch2010). On the contrary, the absence of belowground niche differentiation among species in conservative traits (RDMC and RTD) and %M could be explained by the high intraspecific variability in these traits. This variability may result from the high spatial heterogeneity of soil resources (Weemstra et al. Reference Weemstra, Mommer, Visser, Van Ruijven, Kuyper, Mohren and Sterck2016). For example, the spatial distribution of root-mycorrhizal associations is expected to be driven by P content, a highly variable nutrient in the soil (Cui & Caldwell Reference Cui and Caldwell1996). Furthermore, compaction may exert strong selective pressure, leading a reduced intraspecific variability in D and BI (as mentioned earlier). However, it appears that compaction does not influence conservative traits (RDMC and RTD), which are more associated with resource conservation. As a result, there is no single optimal phenotype of conservative traits (with low intraspecific variability) that responds to compacted soils.

More information is needed to better understand how variations in root traits within and between species contribute to niche differentiation and prioritization of restoration efforts in TDF communities. For example, species such as Ochroma pyramidale (Oh.py), Pseudobombax septenatum (Pse.sep), and Ceiba pentandra (Ce.pe), known for their low wood density and fast growth rates, exhibited thick roots with low density. This efficient strategy allows them to store water and carbohydrates, which is advantageous in dry forest environments (Pineda-García, Paz & Tinoco-Ojanguren, Reference Pineda-García, Paz and Tinoco-Ojanguren2011; Sanaphre-Villanueva et al. Reference Sanaphre-Villanueva, Pineda-García, Dáttilo, Pinzón-Pérez, Ricaño-Rocha and Paz2022). However, it is worth noting that dense wood species like Celtis iguanaea (Ce.ig) and Tabebuia rosea (Ta.ro) also exhibited a similar combination of traits. This suggests that further exploration and study of a wide functional space of species are needed to fully understand the patterns of variation in root traits.

Root traits such as root diameter and branching intensity may be useful for prioritizing species to restore abandoned pastures of TDF regions. For instance, in Ceiba pentandra (Ce.pe), thick roots and low tissue density were associated with water storage. This may be important for the maintenance of root xylem hydration and the water stream from roots to leaves, allowing photosynthesis and growth rates during dry periods at the seasonal or daily scale, during the hours of greatest transpiration (Čermák et al. Reference Čermák, Kučera, Bauerle, Phillips and Hinckley2007; Poorter & Markesteijn Reference Poorter and Markesteijn2008). Several studies have suggested that the large diameter of growing tips helps to deform and separate soil particles, enhancing mechanical force and soil penetration ability (Materechera et al. Reference Materechera, Alston, Kirby and Dexter1992; Atwell Reference Atwell1993; Clarkl et al. Reference Clarkl, Whalleyl and Barraclough2003; Bengough et al. Reference Bengough, Bransby, Hans, McKenna, Roberts and Valentine2006; Weemstra et al. Reference Weemstra, Mommer, Visser, Van Ruijven, Kuyper, Mohren and Sterck2016), which makes species with thick roots promising candidates for establishing at initial stages of forest cover. A perfect example is Chloroleucon mangense (Ch.ma), with thick roots and high fiber and structural carbohydrate contents (Paz obs. Pers.). Additionally, Ch.ma is a nitrogen-fixing legume (Sprent Reference Sprent2001), which may restore soil fertility in degraded drylands, frequently seen in TDF (Avendaño-Yáñez et al. Reference Avendaño-Yáñez, De La, López-Ortiz, Perroni and Pérez-Elizalde2018). Conversely, Casearia corymbosa (Ca.co), Celtis iguanaea (Ce.ig), and Guazuma ulmifolia (Gu.ul), with branched, thin, and high-density roots, are predicted to be efficient in exploring soils and acquiring resources, allowing them to supply the high-water demand of the leaves, as these species have low water potentials during drought periods (Werden et al. Reference Werden, Becknell and Powers2018). However, those species may not develop in compacted soils because their roots cannot easily penetrate dense soils (Clarkl et al. Reference Clarkl, Whalleyl and Barraclough2003); therefore, they are good candidates for restoring sites with low soil compaction.

Here, we highlight these results as essential insights about what traits should be used to select and what can be the possible relations with restoration effectiveness. However, other belowground traits need to be explored. Root depth, elongation rate, and other physiological traits have been identified as critical determinants of plant performance under drought due to allowing access to unexploited soil moisture (Garbowski et al. Reference Garbowski, Avera, Bertram, Courkamp, Gray, Hein, Lawrence, McIntosh, McClelland, Post, Slette, Winkler and Brown2020). Additionally, in TDF, the introduction of exotic grasses and legumes to promote and improve animal forage (Vasquez-Valderrama et al. Reference Vasquez-Valderrama, González-M, López-Camacho, Baptiste and Salgado-Negret2020) may reduce the establishment probability of tree species. Therefore, to explore traits associated with the competitive exclusion of those exotic species may be essential to improve the restoration success (Garbowski et al. Reference Garbowski, Avera, Bertram, Courkamp, Gray, Hein, Lawrence, McIntosh, McClelland, Post, Slette, Winkler and Brown2020). Finally, tree species selection for restoration should not rely only on root traits analysis, but these results must be confirmed by demographic analyses that relate these strategies to species’ performance in the field.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0266467424000129.

Acknowledgments

We acknowledge Enel Colombia and Natura Foundation and its local team from the “Ecological restoration plan of the tropical dry forest of the El Quimbo Hydroelectric plant” (“Plan de restauración ecológica de bosque seco tropical de la Central Hidroeléctrica El Quimbo”) for all of their support in carrying out this investigation.

Financial support

This research was supported by the project “¿Cómo optimizar los esfuerzos de restauración del bosque seco? un análisis desde el paisaje y los rasgos funcionales de las especies” funded by the “Convocatoria nacional para el fomento de alianzas interdisciplinarias que articulen investigación, creación, extensión y formación”, grant of the Universidad Nacional de Colombia 20192021. Rosa Arrieta was supported by the “Colombia Biodiversa” grant no 09-2021 provided by the Alejandro Angel Escobar Foundation.

References

Alameda, D and Villar, R (2012) Linking root traits to plant physiology and growth in Fraxinus angustifolia Vahl. seedlings under soil compaction conditions. Environmental and Experimental Botany 79, 4957.CrossRefGoogle Scholar
Arrieta-González, R, Paez, J, Dominguez-Haydar, Y and Salgado-Negret, B (2021) Limited evidence of coupling between above and belowground functional traits in tropical dry forest seedlings. Revista de Biología Tropical 69, 763771.CrossRefGoogle Scholar
Asmelash, F, Bekele, T and Belay, Z (2019) Comparative field survival and growth of selected Ethiopian native tree species and the effect of whole soil arbuscular mycorrhizal fungi inoculation. Journal of Horticulture and Forestry 11, 1931.Google Scholar
Atwell, BJ (1993) Response of roots to mechanical impedance. Environmental and Experimental Botany 33, 2740.CrossRefGoogle Scholar
Avella-M, A, García-G, N, Fajardo-Gutiérrez, F, González-Melo, A, Avella-M, A, García-G, N, Fajardo-Gutiérrez, F and González-Melo, A (2019) Patrones de sucesión secundaria en un bosque seco tropical interandino de Colombia: implicaciones para la restauración ecológica. Caldasia 41, 1227.CrossRefGoogle Scholar
Avendaño-Yáñez, M, De La, L, López-Ortiz, S, Perroni, Y and Pérez-Elizalde, S (2018) Leguminous trees from tropical dry forest generate fertility islands in pastures. Arid Land Research and Management 32, 5770.CrossRefGoogle Scholar
Bahadur, A, Batool, A, Nasir, F, Jiang, S, Mingsen, Q, Zhang, Q, Pan, J, Liu, Y and Feng, H (2019) Mechanistic insights into arbuscular mycorrhizal fungi-mediated drought stress tolerance in plants. International Journal of Molecular Sciences 20, 4199.CrossRefGoogle ScholarPubMed
Bassett, IE, Simcock, RC and Mitchell, ND (2005) Consequences of soil compaction for seedling establishment: Implications for natural regeneration and restoration. Austral Ecology 30, 827833.CrossRefGoogle Scholar
Bates, TR and Lynch, JP (2001) Root hairs confer a competitive advantage under low phosphorus availability. Plant and Soil 236, 243250.CrossRefGoogle Scholar
Batey, T (2009) Soil compaction and soil management-a review. Soil Use and Management 25, 335345.CrossRefGoogle Scholar
Bengough, AG, Bransby, MF, Hans, J, McKenna, SJ, Roberts, TJ and Valentine, TA (2006) Root responses to soil physical conditions; growth dynamics from field to cell. Journal of Experimental Botany 57, 437447.CrossRefGoogle ScholarPubMed
Bergmann, J, Weigelt, A, van der Plas, F, Laughlin, DC, Kuyper, TW, Guerrero-Ramirez, N, Valverde-Barrantes, OJ, Bruelheide, H, Fresche, GT, Iversen, CM, Kattge, J, McCormack, ML, Meier, IC, Rillig, MC, Roumet, C, Semchenko, M, Sweeney, CJ, van Ruijven, J, York, LM and Mommer, L (2020) The fungal collaboration gradient dominates the root economics space in plants. Science Advances 6.CrossRefGoogle ScholarPubMed
Brown, S and Lugo, AE (1982) The storage and production of organic matter in tropical forests and their role in the global carbon cycle. Biotropica 14, 161.CrossRefGoogle Scholar
Brundrett, MC (2002) Coevolution of roots and mycorrhizas of land plants. New Phytologist 154, 275304.CrossRefGoogle ScholarPubMed
Brundrett, MC and Tedersoo, L (2018) Evolutionary history of mycorrhizal symbioses and global host plant diversity. New Phytologist 220, 11081115.CrossRefGoogle ScholarPubMed
Cantarel, AAM, Allard, V, Andrieu, B, Barot, , Enjalbert, , Gervaix, J, Goldringer, I, Pommier, T, Saint-Jean, and Le Roux, X (2021) Plant functional trait variability and trait syndromes among wheat varieties: The footprint of artificial selection. Journal of Experimental Botany 72, 11661180.CrossRefGoogle ScholarPubMed
Carmona, CP, de Bello, F, Mason, NWH and Lep S, J. (2019) Trait probability density (TPD): measuring functional diversity across scales based on TPD with R. Ecology 100.CrossRefGoogle ScholarPubMed
Carmona, CP, de Bello, F, Mason, NWH and Lepš, J (2016) Traits without borders: integrating functional diversity across scales. Trends in Ecology & Evolution 31, 382394.CrossRefGoogle Scholar
Čermák, J, Kučera, J, Bauerle, WL, Phillips, N and Hinckley, TM (2007) Tree water storage and its diurnal dynamics related to sap flow and changes in stem volume in old-growth Douglas-fir trees. Tree Physiology 27:181198.CrossRefGoogle ScholarPubMed
Chen, YL, Palta, J, Clements, J, Buirchell, B, Siddique, KHM and Rengel, Z (2014) Root architecture alteration of narrow-leafed lupin and wheat in response to soil compaction. Field Crops Research 165, 6170.CrossRefGoogle Scholar
Clarkl, LL, Whalleyl, WR and Barraclough, PB (2003) How do roots penetrate strong soil? Plant and Soil 255, 93104.CrossRefGoogle Scholar
Cui, M and Caldwell, MM (1996) Facilitation of plant phosphate acquisition by arbuscular mycorrhizas from enriched soil patches: I. Roots and hyphae exploiting the same soil volume. New Phytologist 133, 453460.CrossRefGoogle Scholar
Cusack, DF, Addo-Danso, SD, Agee, EA, Andersen, KM, Arnaud, M, Batterman, SA, Brearley, FQ, Ciochina, MI, Cordeiro, AL, Dallstream, C, Diaz-Toribio, MH, Dietterich, LH, Fisher, JB, Fleischer, K, Fortunel, C, Fuchslueger, L, Guerrero-Ramírez, NR, Kotowska, MM, Lugli, LF, Marín, C, McCulloch, LA, Maeght, JL, Metcalfe, D, Norby, RJ, Oliveira, RS, Powers, JS, Reichert, T, Smith, SW, Smith-Martin, CM, Soper, FM, Toro, L, Umaña, MN, Valverde-Barrantes, O, Weemstra, M, Werden, LK, Wong, M, Wright, CL, Wright, SJ and Yaffar, D (2021) Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances. Frontiers in Forests and Global Change 4, 704469.CrossRefGoogle Scholar
Damián, X, Ochoa-López, S, Gaxiola, A, Fornoni, J, Domínguez, CA and Boege, K (2020) Natural selection acting on integrated phenotypes: covariance among functional leaf traits increases plant fitness. New Phytologist 225, 546557.CrossRefGoogle ScholarPubMed
Dinno, A (2018) PARAN: Horn’s Test of Principal Components/Factors. R package version 1.5.2. https://CRAN.R-project.org/package=paran Google Scholar
Eissenstat, DM, Kucharski, JM, Zadworny, M, Adams, TS and Koide, RT (2015) Linking root traits to nutrient foraging in arbuscular mycorrhizal trees in a temperate forest. New Phytologist 208, 114124.CrossRefGoogle Scholar
Etter, A, McAlpine, C and Possingham, H (2008) Historical patterns and drivers of landscape change in Colombia since 1500: A regionalized spatial approach. Annals of the Association of American Geographers 98, 223.CrossRefGoogle Scholar
Freschet, GT, Pagès, L, Iversen, CM, Comas, LH, Rewald, B, Roumet, C, Klimešová, J, Zadworny, M, Poorter, H, Postma, JA, Adams, TS, Bagniewska-Zadworna, A, Bengough, AG, Blancaflor, E B, Brunner, I, Cornelissen, JHC, Garnier, E, Gessler, A, Hobbie, SE, Meier, IC, Mommer, L, Picon-Cochard, C, Rose, L, Ryser, P, Scherer-Lorenzen, M, Soudzilovskaia, NA, Stokes, A, Sun, T, Valverde-Barrantes, OJ, Weemstra, M, Weigelt, A, Wurzburger, N, York, LM, Batterman, SA, Gomes de Moraes, M, Janeček, Š, Lambers, H, Salmon, V, Tharayil, N and McCormack, ML (2021) A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements. New Phytologist 232, 9731122.CrossRefGoogle ScholarPubMed
Garbowski, M, Avera, B, Bertram, JH, Courkamp, JS, Gray, J, Hein, KM, Lawrence, R, McIntosh, M, McClelland, S, Post, AK, Slette, IJ, Winkler, DE and Brown, CS (2020) Getting to the root of restoration: considering root traits for improved restoration outcomes under drought and competition. Restoration Ecology 28, 13841395.CrossRefGoogle Scholar
García, H, Corzo, G, Isaacs, P and Etter, A (2014) Distribucion y estado actual de los remanentes del bioma de bosque seco tropical en Colombia: insumos para su gestón. pp. 228251 in Pizano, C. & García Martínez, H. (eds.). El bosque seco tropical en Colombia (1st edition). Instituto de Investigación de Recursos Biológicos Alexander Von Humboldt, Bogotá, Colombia.Google Scholar
Gavito, ME, Pérez-Castillo, D, González-Monterrubio, CF, Vieyra-Hernández, T and Martínez-Trujillo, M (2008) High compatibility between arbuscular mycorrhizal fungal communities and seedlings of different land use types in a tropical dry ecosystem. Mycorrhiza 19, 4760.CrossRefGoogle Scholar
González-M, R, Garcia, H, Isaacs, P, Cuadros, H, López-Camacho, R, Rodriguez, N, Pérez, K, Mijares, F, Castano-Naranjo, A, Jurado, R, Idárraga-Piedrahita, A, Rojas, A, Vergara, H and Pizano, C (2018) Disentangling the environmental heterogeneity, floristic distinctiveness and current threats of tropical dry forests in Colombia. Environmental Research Letters 13, 045007.CrossRefGoogle Scholar
González-M, R, Norden, N, Posada, JM, Pizano, C, García, H, Idárraga-Piedrahita, Á, López-Camacho, R, Nieto, J, Rodríguez-M, GM, Torres, AM, Castaño-Naranjo, A, Jurado, R, Franke-Ante, R, Galindo-T, R, Hernández R, E, Barbosa, A and Salgado-Negret, B (2019) Climate severity and land-cover transformation determine plant community attributes in Colombian dry forests. Biotropica 51, 826837.CrossRefGoogle Scholar
González-M, R, Posada, JM, Carmona, CP, Garzón, F, Salinas, V, Idárraga-Piedrahita, Á, Pizano, C, Avella, A, López-Camacho, R, Norden, N, Nieto, J, Medina, SP, Rodríguez-M, GM, Franke-Ante, R, Torres, AM, Jurado, R, Cuadros, H, Castaño-Naranjo, A, García, H and Salgado-Negret, B 2021. Diverging functional strategies but high sensitivity to an extreme drought in tropical dry forests. Ecology Letters 24, 451463.CrossRefGoogle Scholar
Horn, JL (1965) A rationale and test for the number of factors in factor analysis. Psychometrika 30, 179185. https://doi.org/10.1007/BF02289447 CrossRefGoogle ScholarPubMed
Jie, C., Jing-Zhang, C., Man-Zhi, T. & Zi-Tong, G. 2002. Soil degradation: a global problem endangering sustainable development. Journal of Geographical Sciences 12, 243252.CrossRefGoogle Scholar
Kong, D, Ma, C, Zhang, Q, Li, L, Chen, X, Zeng, H and Guo, D (2014) Leading dimensions in absorptive root trait variation across 96 subtropical forest species. New Phytologist 203, 863872.CrossRefGoogle ScholarPubMed
Lugli, LF, Andersen, KM, Aragão, LEOC, Cordeiro, AL, Cunha, HFV, Fuchslueger, L, Meir, P, Mercado, LM, Oblitas, E, Quesada, CA, Rosa, JS, Schaap, KJ, Valverde-Barrantes, O and Hartley, IP (2020) Multiple phosphorus acquisition strategies adopted by fine roots in low-fertility soils in Central Amazonia. Plant and Soil 450, 4963.CrossRefGoogle Scholar
Lux, A, Luxová, M, Abe, J and Morita, S (2004) Root cortex: structural and functional variability and responses to environmental stress. Root Research 13, 117131.CrossRefGoogle Scholar
Ma, Z, Guo, D, Xu, X, Lu, M, Bardgett, RD, Eissenstat, DM, McCormack, ML and Hedin, LO (2018) Evolutionary history resolves global organization of root functional traits. Nature 555, 9497.CrossRefGoogle ScholarPubMed
Materechera, SA, Alston, AM, Kirby, JM and Dexter, AR (1992) Influence of root diameter on the penetration of seminal roots into a compacted subsoil. Plant and Soil 144, 297303.CrossRefGoogle Scholar
McCormack, LM, Adams, TS, Smithwick, EAH and Eissenstat, DM (2012) Predicting fine root lifespan from plant functional traits in temperate trees. New Phytologist 195, 823831.CrossRefGoogle Scholar
McCormack, ML, Dickie, IA, Eissenstat, DM, Fahey, TJ, Fernandez, CW, Guo, D, Helmisaari, HS, Hobbie, EA, Iversen, CM, Jackson, RB, Leppälammi-Kujansuu, J, Norby, RJ, Phillips, RP, Pregitzer, KS, Pritchard, SG, Rewald, B and Zadworny, M (2015) Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes. New Phytologist 207, 505518.CrossRefGoogle ScholarPubMed
McCormack, ML and Iversen, CM (2019) Physical and Functional Constraints on Viable Belowground Acquisition Strategies. Frontiers in Plant Science 10, 474507.CrossRefGoogle ScholarPubMed
McGonigle, TP, Miller, MH, Evans, DG, Fairchild, GL and Swan, JA (1990) A new method which gives an objective measure of colonization of roots by vesicular—arbuscular mycorrhizal fungi. New Phytologist 115, 495501.CrossRefGoogle ScholarPubMed
Miles, L, Newton, AC, Defries, RS, Ravilious, C, May, I, Blyth, S, Kapos, V and Gordon, JE (2006) A global overview of the conservation status of tropical dry forests. Journal of Biogeography 33, 491505.CrossRefGoogle Scholar
Ostonen, I, Püttsepp, Ü, Biel, C, Alberton, O, Bakker, MR, Lõhmus, K, Majdi, H, Metcalfe, D, Olsthoorn, AFM, Pronk, A, Vanguelova, E, Weih, M and Brunner, I (2007) Specific root length as an indicator of environmental change. Plant Biosystems 141, 426442.CrossRefGoogle Scholar
Paz, H, Pineda-García, F and Pinzón-Pérez, LF (2015) Root depth and morphology in response to soil drought: comparing ecological groups along the secondary succession in a tropical dry forest. Oecologia 179, 551561.CrossRefGoogle Scholar
Pineda-García, F, Paz, H, Tinoco-Ojanguren, C (2011) Morphological and physiological differentiation of seedlings between dry and wet habitats in a tropical dry forest: water-use strategies of TDF tree seedlings. Plant, Cell & Environment 34, 15361547.CrossRefGoogle Scholar
Poorter, L and Markesteijn, L (2008) Seedling Traits Determine Drought Tolerance of Tropical Tree Species. Biotropica 40, 321331.CrossRefGoogle Scholar
Portillo-Quintero, CA and Sánchez-Azofeifa, GA (2010) Extent and conservation of tropical dry forests in the Americas. Biological Conservation 143, 144155.CrossRefGoogle Scholar
Raven, JA and Edwards, D (2001) Roots: evolutionary origins and biogeochemical significance. Journal of Experimental Botany 52, 381401.CrossRefGoogle ScholarPubMed
R Core Team (2021) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Reich, PB, Wright, IJ, Cavender-Bares, J, Craine, JM, Oleksyn, J, Westoby, M and Walters, MB (2003) The evolution of plant functional variation: Traits, spectra, and strategies. International Journal of Plant Sciences 164.CrossRefGoogle Scholar
Rodrigues, RR, Lima, RAF, Gandolfi, S and Nave, AG (2009) On the restoration of high diversity forests: 30 years of experience in the Brazilian Atlantic Forest. Biological Conservation 142, 12421251.CrossRefGoogle Scholar
Sala, A, Piper, F and Hoch, G (2010) Physiological mechanisms of drought-induced tree mortality are far from being resolved. The New Phytologist 186, 274281.CrossRefGoogle ScholarPubMed
Salgado-Negret, B, Pulido-Rodríguez, EN, Cabrera, M, Osorio, CR and Paz, H (2016) Protocolo para la medición de rasgos funcionales en plantas. In Salgado-Negret, B. (Ed.), La ecología funcional como aproximación al estudio, manejo y conservación de la biodiversidad: protocolos y aplicaciones (pp. 12–35). Instituto de Investigaciones de Recursos Biológicos Alexander von Humboldt, Colombia.Google Scholar
Sanaphre-Villanueva, L, Pineda-García, F, Dáttilo, W, Pinzón-Pérez, LF, Ricaño-Rocha, A and Paz, H (2022) Above- and below-ground trait coordination in tree seedlings depend on the most limiting resource: a test comparing a wet and a dry tropical forest in Mexico. PeerJ 10, e13458.CrossRefGoogle Scholar
Seethepalli, A, Dhakal, K, Griffiths, M, Guo, H, Freschet, GT and York, LM (2021) RhizoVision Explorer: Open-source software for root image analysis and measurement standardization. AoB PLANTS 13.CrossRefGoogle ScholarPubMed
Siqueira, JO and Saggin-Júnior, OJ (2001) Dependency on arbuscular mycorrhizal fungi and responsiveness of some Brazilian native woody species. Mycorrhiza 11, 245255.CrossRefGoogle Scholar
Smith, J and Read, DJ (2009) Mycorrhizal Symbiosis. Soil Science Society of America Journal - SSSAJ 73.Google Scholar
Sprent, JI (2001) Nodulation in Legumes. United Kingdom: Kew Publishing. 146 pp.Google Scholar
Torres-Rodríguez, S, Díaz-Triana, JE, Villota, A, Gómez, W and Avella-M, A (2019) Diagnóstico ecológico, formulación e implementación de estrategias para la restauración de un bosque seco tropical interandino (Huila, Colombia). Caldasia 41, 4259.CrossRefGoogle Scholar
Tracy, SR, Black, CR, Roberts, JA and Mooney, SJ (2011) Soil compaction: a review of past and present techniques for investigating effects on root growth. Journal of the Science of Food and Agriculture 91, 15281537.CrossRefGoogle ScholarPubMed
Umaña, MN, Zhang, C, Cao, M, Lin, L and Swenson, NG (2015) Commonness, rarity, and intraspecific variation in traits and performance in tropical tree seedlings. Ecology Letters 18, 13291337.CrossRefGoogle ScholarPubMed
Valverde-Barrantes, OJ, Freschet, GT, Roumet, C and Blackwood, CB (2017) A worldview of root traits: the influence of ancestry, growth form, climate and mycorrhizal association on the functional trait variation of fine-root tissues in seed plants. New Phytologist 215, 15621573.CrossRefGoogle ScholarPubMed
Vasquez-Valderrama, M, González-M, R, López-Camacho, R, Baptiste, MP and Salgado-Negret, B. (2020) Impact of invasive species on soil hydraulic properties: importance of functional traits. Biological Invasions 22, 18491863.CrossRefGoogle Scholar
Vitousek, PM (2004) Nutrient Cycling and Limitation: Hawai’i as a Model System. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Weemstra, M, Mommer, L, Visser, EJW, Van Ruijven, J, Kuyper, TW, Mohren, GMJ and Sterck, FJ (2016) Towards a multidimensional root trait framework: a tree root review. New Phytologist 211, 11591169.CrossRefGoogle ScholarPubMed
Weemstra, M, Valverde-Barrantes, OJ, Fortunel, C, Oblitas Mendoza, EM, Prata, EM, Vásquez Pilco, M, Vicentini, A, Vleminckx, J and Baraloto, C (2023) Weak phylogenetic and habitat effects on root trait variation of 218 neotropical tree species. Frontiers in Forests and Global Change 6, 1187127.CrossRefGoogle Scholar
Werden, LK, Becknell, JM and Powers, JS (2018) Edaphic factors, successional status and functional traits drive habitat associations of trees in naturally regenerating tropical dry forests. Functional Ecology 32, 27662776.CrossRefGoogle Scholar
Werden, LK, Zarges, S, Holl, KD, Oliver, CL, Oviedo-Brenes, F, Rosales, JA and Zahawi, RA (2022) Assisted restoration interventions drive functional recovery of tropical wet forest tree communities. Frontiers in Forests and Global Change 5, 935011.CrossRefGoogle Scholar
Zangaro, W, Bononi, VLR and Trufen, SB (2000) Mycorrhizal dependency, inoculum potential and habitat preference of native woody species in South Brazil. Journal of Tropical Ecology 16, 603622.CrossRefGoogle Scholar
Figure 0

Table 1. Tree species studied in a tropical dry forest in Huila, Colombia. Family, common name, code, leaf habitat, and wood density (WD) per species. Range (min-max) and mean (in parenthesis) for height (H) and diameter at breast height (DBH) of trees sampled per species. *Wood density was obtained from Gonzalez et al. (2021)

Figure 1

Table 2. Functional traits measured and their functional significance

Figure 2

Figure 1. Pearson correlation coefficients with Bonferroni correction for pairwise relationships among six fine root traits. Significant correlations are indicated as red (negative) and blue (positive) ovals. Trait abbreviations: D: root diameter, %M: mycorrhizal colonization, RDMC: root dry matter content, RTD: root tissue density, BI: branching intensity, SRL: specific root length.

Figure 3

Figure 2. Multivariate trait analysis. (a) PCA of six fine root traits. Each point in the PCA is an individual of a given species; color codes are shown in panel (b). Trait abbreviations: D: root diameter, BI: branching intensity, SRL: specific root length, RDMC: root dry matter content, RTD: root tissue density, %M: mycorrhizal colonization. (b) Trait probability densities (TPD) showing the functional trait combinations for eleven tree species. Species abbreviations are in Table 1; each species has a distinctive color in the PCA and TPD plots. Different letters in parenthesis next to the species abbreviation indicate significant differences between species using the dissimilarity index (>95% non-shared probability).

Figure 4

Figure 3. Trait probability density for each of the 6 fine root traits and for the 11 tree species. The Y axis is the density. Trait abbreviations: D: root diameter, BI: branching intensity, SRL: specific root length, RDMC: root dry matter content, RTD: root tissue density, %M: mycorrhizal colonization. Species abbreviations are in Table 1. Different letters in parenthesis next to species abbreviations indicate significant differences between species according to the similarity index.

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