Next Article in Journal
Floristic Diversity, Indicator and Suitable Species for Andean Livestock in the Sillapata Micro-Watershed, Acopalca
Previous Article in Journal
Exploring the Potential of Biocontrol Agent Against Root and Stem Rot Disease in Durian (Durio zibethinus)
Previous Article in Special Issue
Pollination and Essential Oil Production of Lavandula angustifolia Mill. (Lamiaceae)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJPB
Volume 16
Issue 3
10.3390/ijpb16030076
ijpb-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Interactive Effect of Copper and Herbivory on the Whole-Plant Growth of Leucaena leucocephala

by
Shirley Margarita Amaya-Martín
1,
Horacio Salomón Ballina-Gómez
1,*,
Esaú Ruíz-Sánchez
1,
Gabriel Jesús Azcorra-Perera
1,
Roberto Rafael Ruiz-Santiago
2 and
Jacques Fils Pierre
3
1
Tecnológico Nacional de México/IT de Conkal, División de Estudios de Posgrado e Investigación, Mérida 97345, Yucatán, Mexico
2
SECIHTI-Laboratorio Regional para el Estudio y Conservación de Germoplasma (GermoLab), Centro de Investigación Científica de Yucatán, Parque Científico y Tecnológico de Yucatán, Km. 5.5, Carretera, Sierra Papacal-Chuburná Puerto, Mérida 97302, Yucatán, Mexico
3
International Fertiliser Development Center (IFDC), Muscle Shoals, AL 35662, USA
*
Author to whom correspondence should be addressed.
Int. J. Plant Biol. 2025, 16(3), 76; https://doi.org/10.3390/ijpb16030076
Submission received: 16 May 2025 / Revised: 19 June 2025 / Accepted: 4 July 2025 / Published: 6 July 2025
(This article belongs to the Special Issue Plant Resistance to Insects)
Browse Figures
Versions Notes

Abstract

This study investigated how Leucaena leucocephala, a dry forest plant, copes with soil copper and herbivory caused by Schistocerca piceifrons, crucial for understanding species adaptation in stressed environments. A 33-day factorial experiment with three copper and two herbivory treatments assessed seedling growth rates (relative growth rate of biomass—RGRB, and leaf area—RGRLA), morphology, net assimilation rate (NAR), biomass allocation, and survival. Seedlings demonstrated compensatory growth in terms of RGRB and RGRLA under high copper and herbivory. Although copper decreased overall survival, surviving individuals effectively compensated for herbivory damage. These tolerance responses, primarily driven by an increased NAR (accounting for 98% of compensation), aligned with the limiting resource model. While most morphological components remained stable, herbivory specifically increased the root–shoot ratio. These findings indicate L. leucocephala possesses significant resilience through physiological adjustments, like enhancing NAR, and biomass reallocation strategies, allowing it to persist despite multiple stressors common in dry forests.

1. Introduction

Rapid industrial development and the incessant growth of the human population have generated serious environmental problems, including those caused by heavy metals [1]. When these metals enter the food chain, they pose a severe threat to organisms, even at low concentrations [2,3]. Copper (Cu), a widely used industrial metal, is one example of a heavy metal. It is employed in the production of enamels, pigments, tanning reagents, algaecides, and agrochemicals [4], as well as being used as a growth promoter and antimicrobial agent [5,6]. Owing to its persistence (non-biodegradability), it can accumulate on surfaces and then be absorbed by plants in ionic, complex, and exchangeable cation forms [5,6]. This may lead to impaired growth and reduced biomass production [7], as well as interfere with biomass allocation, which optimizes resource use [8]. These phenomena manifest differently in each species due to intrinsic growth factors [9]. Cu inhibits root and sprout growth by altering biochemical and physiological processes [4,9,10], resulting from reduced cell division and structural damage or death of cells in the apical meristems [11,12]. Additionally, when Cu induces lignification and cell wall stiffening, the cellular expansion process is affected, leading to reduced root and stem diameter and decreased leaf growth [4]. In addition to soil contamination by Cu, plants also face selective pressure from herbivorous insects [13]. Several studies have explored the effects of herbivory on plants [14,15,16,17,18], with mixed results, although some show a reduction in plant growth [17]. Different hypotheses have been proposed to explain these outcomes. One of them is the Growth Rate Model GRM [19], which suggests that plant compensatory growth would be greater in response to herbivory in resource-limited environments. This is because plants in such environments do not reach their potential maximum growth rates [20]. On the other hand, Ref. [21] introduced the Compensatory Continuum Hypothesis (CCH), proposing that plants will better compensate for herbivory damage as the availability of a specific resource (light, water, nutrients) increase. Meanwhile, Ref. [22] developed the Limiting Resource Model (LRM), which posits seven possible scenarios involving two types of resources (focal and alternate), three types of compensatory growth responses (low, neutral, and high), and environments with contrasting resource levels.
Although plant compensatory responses to herbivory have been well studied [23,24], very few studies have focused on explaining these responses through total plant growth [17,25]. In the study by Ballina-Gómez et al. [17], it was proposed that plant compensatory responses might be a function of a synergistic effect produced by the plant’s total growth, rather than being expressed in isolated growth variables.
Considering that one of the most comprehensive measures of growth is the Relative Growth Rate RGR [26,27], which is influenced by both morphological and physiological components (leaf area ratio: LAR; specific leaf area: SLA; net assimilation rate: NAR), it is likely that a better understanding of plant compensatory responses to herbivory can be achieved through a combination of these components.
This study focuses on evaluating the growth responses of Leucaena leucocephala to the toxic effects of Cu and herbivory by the acridid Schistocerca piceifrons under experimental conditions. This acridid is an economically significant pest in the Yucatan Peninsula, Mexico. Four main questions were posed: (i) Are the growth and survival of L. leucocephala seedlings affected by Cu in the soil and herbivory by Sch. piceifrons?; (ii) Are the compensatory responses of L. leucocephala consistent with models proposed in the literature?; (iii) Which morphological and physiological components of the growth rate are involved in the compensatory response of L. leucocephala?; and (iv) How does biomass allocation vary under exposure to Cu in the soil and herbivory?
To answer these questions, we studied the Relative Growth Rate (RGR) and its morphological (LAR, SLA) and physiological (NAR) components, as well as the biomass allocation of each plant (LWR, SWR, RWR, R). Different doses of Cu and natural herbivory were applied. Both species were selected due to their natural interaction in the lowlands of the Yucatan Peninsula. Although studies on herbivory have typically been conducted in rainforests, it has been found that damage caused by herbivorous insects is a frequent phenomenon in lowlands >40% [17,18]. Additionally, it is well known that Cu is a prevalent heavy metal in Yucatan Peninsula soils. This metal may be present in the leaves, stems, and roots of Leucaena leucocephala, a dominant species of the lowlands [28,29].
Based on these considerations, we hypothesize the following: (1) High concentrations of Cu in the soil and herbivory by Sch. piceifrons will decrease the growth (in terms of RGRB, RGRAF, and leaf production rate) and survival of L. leucocephala; (2) The Limiting Resource Model will best explain responses to adverse conditions such as increased Cu in the soil and herbivory [22]; (3) Since L. leucocephala is classified as a fast-growing species [30], its relative growth rate (RGRB) will likely depend on net assimilation rate (NAR) and specific leaf area SLA [31]; and (4) Biomass allocation patterns will be strongly influenced by damage to plant structures (due to Cu exposure, [32]; and herbivory, [33]).

2. Materials and Methods

2.1. Study Site and Species

This study was conducted at the Laboratory of Botany at the Instituto Tecnológico de Conkal (ITC), Yucatan, Mexico. Plant material was collected from a deciduous forest surrounding the ITC, which is located 10 m above sea level, with an average temperature ranging from 26 to 27.6 °C and annual precipitation between 728.2 and 1000 mm [34,35]. The dominant species include Vachellia pennatula (Fern-leaf acacia), Caesalpinia gaumeri (Kitim che’), Sphinga platyloba (Muk), Lysiloma latisiliquum (Wild tamarind), Enterolobium cyclocarpum (Guanacaste), Mimosa bahamensis (Sak-catzin), Spondias mombin (Yellow mombin), Metopium brownie (Chechem), Cochlospermum vitifolium (Buttercup tree), Guazuma ulmifolia (West Indian elm), Trema micrantha (Jamaican nettletree), Annona reticulata (Custard apple), Gyrocarpus americanus (Helicopter tree), Piscidia piscipula (Fish-poison tree), Pithecellobium dulce (Madras thorn), and Havardia albicans (Chucum) [36,37,38].
Seeds were collected from ten parental trees of Leucaena leucocephala (Fabaceae) ranging in height from 5 to 20 m [30] and with diameters at breast height (dbh) from 10 to 25 cm [38,39]. The seeds were sown in plastic trays containing sterile soil and placed inside the laboratory to grow experimental seedlings. Soil sterilization was performed using the vaporization method (Caldera No.-08-3095, Sioux Corporation, Bresford, SD, USA) to prevent the growth of vesicular-arbuscular fungal spores and nitrogen-fixing bacteria. The seedlings were then transplanted individually into plastic trays (15 × 10 cm). Both seeds and seedlings were irrigated every other day, and an organic fungicide (copper oxychloride 0.9 g L−1 water) was applied to prevent infections by phytopathogenic fungi.
The soil type was a Leptosol with pH, 7.7; electric conductivity (1:5), 0.24 dS/m−1; cation exchange capacity, 52 meq 100 g−1; organic matter, 20%; N, 1.03%; P, 22.2 mg kg−1; K, 2.6, Ca, 45, Mg, 2.6, and Cu, 0.32 cmol (+) kg−1) as determined by Borges-Gómez et al. [40].
From the population of seedlings, 80–90 days (d) old, intermediate-sized individuals were selected, while extremes were excluded [41].

2.2. Experimental Design

A factorial design involving three Cu treatments × two herbivory treatments (n = 6–12 individuals per treatment) was used. The Cu treatments included: a control treatment without Cu (Cu = 0), a treatment with Cu (SO4 Cu) at a dose of 0.5 g kg−1, and a treatment with duplicated Cu (SO4 Cu) at a dose of 1.0 g kg−1. The herbivory treatments consisted of a control group without exposure to herbivory and a group exposed to herbivory (with 40–60% of the area removed) which was determined by methodology of [42]. Cu was applied to the base of each seedling’s stem. Thirty-one days after exposure to Cu, six seedlings from each treatment group were selected. The seedlings were placed in an air vent (40 cm in height and 60 cm in diameter), where two individuals of Sch. piceifrons were introduced for 24 h. Prior to the insect introduction, the acridids were deprived of food for 24 h. We recorded only seedling survival or mortality (influenced by Cu treatments) during the first 25 days of the experiment. The insects used in the study were adults, obtained from the Comité Estatal de Sanidad Vegetal de Yucatán (CESVY). The experiment lasted 33 days—25 days for plant exposure to Cu and 8 days for the evaluation of the early response to herbivory.
The traits of the seedlings evaluated at the beginning (10 seedlings per treatment) and at the end (6–12 seedlings per treatment) of the experiment included biomass growth, leaf area, and leaf number. Biomass measurements were obtained separately for leaves, stems, and roots by drying them at 55 °C for 48 h or until a constant weight was reached. Leaf area was estimated using digital photos analyzed with ImageJ software version 1.54g [43].
The environmental conditions (mean ± SD) during the experiment were as follows: temperature 25.9 ± 1.41 °C, relative humidity (RH) 81 ± 7.74% (measured using a digital thermohygrometer, model 4096, Control Company Inc., Friendswood, TX, USA), and photosynthetic photon flux density (PPFD; measured with a Li-250A, Li-Cor, Lincoln, NE, USA) 1.28 ± 0.35 (%) mol m−2 d−1. Soil pH (mean ± SE; measured with a potentiometer, Oakton pH/mV/C meter, USA) for the treatments was as follows: control Cu-without herbivory = 6.5 ± 0.19, Cu = 5.7 ± 0.18, and Cu+ = 5.7 ± 0.2; control Cu-with herbivory = 6.2 ± 0.18, Cu = 6.7 ± 0.24, and Cu+ = 6.5 ± 0.18.

2.3. RGRB Estimation: Morphological and Physiological Components

Using the initial and final measurements from the experiment, the following growth indexes were calculated: relative growth rate in biomass (RGRB; g g−1 d−1) and in leaf area (RGRLA; cm2 cm−2 d−1), leaf production rate (LPR: number of leaves), leaf area ratio (LAR: cm2 g−1), specific leaf area (SLA; cm2 g−1), leaf weight ratio (LWR; g g−1), stem weight ratio (SWR; g g−1), root weight ratio (RWR; g g−1), root:shoot ratio (R; g g−1), and net assimilation rate (NAR; mg mm−2 d−1) [31].

2.4. Data Analysis

To determine the effects of Cu and herbivory on L. leucocephala seedling growth, generalized linear models GLM [44] were used. Plant growth for the 10 response variables was analyzed under a factorial analysis structure with two factors: inter-subject factor (three Cu treatments) and intra-subject factor (two herbivory treatments). RGRB, RGRLA, LPR, LWR, SWR, RWR, and R:S were analyzed using a Normal probabilistic model with an identity link function. While LAR, SLA and NAR were analyzed with a Gamma probabilistic model with a log link function.
The survival probability of L. leucocephala seedlings was estimated 25 days after the start of the experiment, using control levels as a reference. A logistic regression model was applied, with survival as the response variable and Cu treatment (categorical) and time (covariate) as independent variables. The model coefficients were estimated, and the Wald χ2 statistic was used under the maximum likelihood method to test the effects of Cu and time factors on survival. These analyses were conducted in SPSS 22 [45]. Path analyses were performed to examine the potential direct and indirect relationships between RGRB (endogenous variable), morphological components LAR, SLA, and LWR, and the physiological component NAR (exogenous variables). The model was adjusted using χ2 analysis (p > 0.05) and AIC values [46]. This analysis was performed in Amos 4.0 (Amos Development Corporation, Crawfordsville, FL, USA).

3. Results

3.1. Effects of Cu and Herbivory on the Growth and Survival of L. leucocephala Seedlings

No factor significantly influenced RGRB (Figure 1A). However, the Cu × herbivory interaction was significant for RGRLA, while the factors did not differ as independent effects (Figure 1B; Table 1). Leaf production rate (LPR) was significantly affected only by herbivory, with higher rates in the control treatment (Figure 1C).
The survival of L. leucocephala seedlings exposed to Cu treatments differed significantly among the treatments (Table 2). During the first 10 days, seedling survival was higher with intermediate Cu application. However, after the 11th day, survival began to decline in the Cu treatments. By the 25th day, survival had decreased to 30% and 45% in both the Cu and Cu+ treatments (Figure 2).

3.2. Effects of Cu and Herbivory on Morphological and Physiological Components of RGRB

Only SLA was significantly influenced by both the Cu × herbivory interaction and by the individual factors (Figure 1E). LAR and NAR showed no significant changes due to either factor or their interaction (Figure 1D,F).
The behavior of the morphological and physiological components across herbivory and Cu treatments did not show substantial variation; therefore, samples were combined without considering treatment differences, and a cause–effect model was developed. The physiological component NAR had a significant positive influence on RGRB (98%). Although other morphological components like SLA and LWR also showed some influence, these were not significant (Figure 3). Similarly, the negative paired correlations among components such as NAR, SLA, and LWR were not significant (Figure 3).

3.3. Effect of Cu and Herbivory on Mass Allocation in Seedlings of L. leucocephala

In R:S, only the Cu × herbivory interaction was significant, and herbivory alone significantly influenced this interaction (Figure 4D). Herbivory also had a significant effect on LWR, which was higher in the control seedling group (Figure 4A). Stem and root allocation (SWR and RWR, respectively) did not vary with Cu or herbivory treatments (Figure 4B,C).

4. Discussion

4.1. Compensatory Growth and Survival of L. leucocephala in Response to Cu Effects

The present study demonstrates the ability of L. leucocephala to compensate for its growth, in terms of RGRB and RGRLA, in response to high concentrations of Cu in the soil—even over a short response time—as demonstrated by Ballina-Gómez et al. [17] with another woody tropical species. Although other studies have reported growth compensation in L. leucocephala due to the presence of Cu in the soil [28,29,47,48,49], few studies have tested the effects of herbivory [50,51]. For that reason, this study focuses strongly on how seedlings specifically respond to these stressors. Similarly, Nanthavong and Sampanpanish [52] showed that Mimosa pudica (Fabaceae) plants exposed to arsenic contamination were able to offset their growth, as estimated by RGRB. In contrast, Marozzi et al. [53] found that Pistia stratiotes (Araceae) did not alter its growth in the presence of lead (Pb).
It is important to consider the low doses of Cu, as such doses may stimulate growth, unlike high doses, which can be toxic [28]. On the other hand, although the decrease in seedling growth (in terms of RGRB) was not significant in the Cu treatments, lower values were observed. This is understandable, as the accumulation of heavy metals in plant tissues leads to lower biomass allocation, since energy is primarily used for adaptation mechanisms in response to high concentrations of the metal [47,54].
While the survival of L. leucocephala was affected as the dose of Cu increased, it was observed that surviving plants managed to compensate for herbivory damage, as proposed by Freeman et al. [55], who obtained similar results with Brassica juncea and Stanleya pinnata. They related these results to the elemental defense hypothesis, which posits that hyper-accumulation has evolved as a protection against herbivores or infections. The similarity in results may suggest the effectiveness of L. leucocephala as a hyper-accumulator species when tolerating Cu and herbivory, rather than just as a useful species for bioremediation [28].
We considered three models proposed to explain the relationship between resource availability and compensatory growth responses to herbivory. By comparing the three models of RGRB, RGRLA, and LPR growth responses, we found that the most useful model to explain these responses was the LRM. This model could explain all the responses when considering the differences in resource availability, Cu, and herbivory. Our results align with those reported by [17,56], who identified LRM as the best model for explaining plant tolerance to herbivory.
When analyzing the CCH, which posits that in high-resource-availability environments, plants may have a greater ability to respond to herbivory than in low-resource-availability environments [21], we found our results similar to those of a meta-analysis examining 11 responses of compensatory growth. In that analysis, no support was found for the GRM, but 10 studies supported the CCH [57]. However, the heterogeneous results obtained among the compensatory models may indicate a more complex relationship between tolerance and the levels of Cu used, unless the genetic stock of the species is known [58].
The LRM is particularly useful for understanding various stress tolerance scenarios, especially in limited resource environments [59]. Our results suggest that only the RGRLA of L. leucocephala supported the CCH. However, this finding was consistent with the LRM scenario, suggesting that herbivory increased Cu acquisition in the soil, resulting in overcompensatory growth in environments with high Cu availability [57,60]. The growth stimulation in L. leucocephala at low concentrations of Cu (20 mg kg−1) has been reported previously [28]; however, in our study, these effects were observed at high concentrations (>200 mg kg−1). This demonstrates the potential of this species as a tolerant plant to Cu in the soil.

4.2. Contribution of Morphological and Physiological Components to the RGRB of L. leucocephala

Several studies have demonstrated the predominant role of morphological and physiological components in the growth of plant species, mostly focusing on the effects of variation among species [61], salinity stress [62], light availability [63], herbivory [17,64,65], mycorrhizal fungi [66], and water availability [67]. However, few studies have addressed the effects of heavy metals, with notable examples being Gandhi et al. [68] and Ali et al. [69]. In this study, we present empirical evidence to explain the role of morphological and physiological components of RGRB in the growth responses of L. leucocephala to a heavy metal (Cu). Generally, the morphological component of greatest importance for RGRB is the SLA [70,71,72,73,74], which is contrary to our results; in this study, the component with the most significant influence was NAR (98%). This suggests a modification in the efficiency of the photosynthetic apparatus, stimulated by Cu [75]. Such modification may reduce the quantity of chlorophyll and carotenoids, negatively affecting photosynthetic efficiency [76,77,78]. Additionally, the internal mechanisms of the plant may activate its ability to avoid and/or tolerate Cu stress, thereby preventing metal translocation to the aerial parts of the plant [47,79].
On the other hand, herbivory by Sch. piceifrons did not produce any variation in the morphological and physiological components of RGRB. These findings contrast with those of Camargo et al. [24] regarding Datura stramonium, which reported an increase in NAR after a simulated herbivory event. Similarly, Ballina-Gómez et al. [17] Carrillo-Herrera et al. [65] found an increase in NAR after simulated herbivory in Brosimum alicastrum and Vitis tiliifolia, but a decrease in leaf area (LAR).

4.3. Mass Allocation in L. leucocephala

As a general pattern, we found that biomass allocation decreased in the following order: SWR, RWR, and LWR. In certain tropical forests, it has been documented that plant species exhibit patterns similar to those observed in our study [80]. When analyzing biomass allocation in plant structures, only the LWR varied significantly due to the effects of herbivory, while SWR and RWR were not affected. These findings are similar to those reported by Huu Thanh et al. [81], who evaluated growth in four species (Bidens pilosa, Ludwigia adscendens, Ludwigia octovalvis, and Ipomoea aquatica). The decrease in LWR in seedlings that experienced herbivory and were in environments with high Cu concentrations suggests a structural reallocation [8,82] of biomass from stems (SWR) to leaves (LWR). This result was confirmed by the high biomass proportion allocated to roots and stems (R:S) in plants affected by herbivory [31]. Additionally, Hackett et al. [83] found that herbivory caused by the aphid Macrosiphum euphorbiae on potato plants significantly altered biomass allocation, leading to an increase in stem biomass. Although minor, the effects of copper on the increase in mass allocation from roots to leaves have also been reported in Leucanthemum vulgare [8].
Overall, the biomass allocation in leaves (LWR), stems (SWR), and roots (RWR) of L. leucocephala supports the idea that seedling responses to herbivory are a function of a synergistic response among different plant structures [16,23]. Furthermore, the total growth responses (RGRB) were based on NAR, a physiological component closely related to the photosynthetic rate [84,85], rather than on the deployment of leaf area (SLA and LWR).
L. leucocephala seedlings exhibited compensatory growth in terms of RGRB and RGRAF in the presence of high levels of Cu and herbivory damage. These tolerance responses were best explained by the limiting resource model (LMR). Seedling survival decreased as a result of Cu in the soil; however, the seedlings demonstrated compensatory responses following herbivore damage. The contamination of L. leucocephala by Cu and herbivory damage did not significantly impact the morphological and physiological components; nevertheless, the net assimilation rate (NAR) drove the compensatory growth responses through RGRB. The mass allocation was only affected in terms of R:S, which increased when seedlings were subjected to herbivory damage.

Author Contributions

Conceptualization: S.M.A.-M. and H.S.B.-G.; Methodology: S.M.A.-M., H.S.B.-G. and E.R.-S.; Investigation: S.M.A.-M., G.J.A.-P. and J.F.P.; Formal Analysis: S.M.A.-M., H.S.B.-G. and R.R.R.-S.; Writing—original draft preparation: S.M.A.-M. and H.S.B.-G.; Funding acquisition: S.M.A.-M. and H.S.B.-G. Writing—review & editing: All authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

We thank Raúl Jiménez Cauich for his assistance with the experiments and Mario Poot from CESVY for supplying adult locusts. S. Amaya-Martín acknowledges the fellowship provided by the Coordinación Nacional de Becas de Educación Superior (CNBES), a program of the Secretaría de Educación Pública (SEP).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
RGRGrowth Rate
RGRBRelative Growth Rate in Biomass
RGRLARelative Growth Rate in Leaf Area
LARLeaf Area Ratio
SLASpecific Leaf Area
NARNet Assimilation Rate
LWRLeaf Weight Ratio
SWRStem Weight Ratio
RWRRoot Weight Ratio
R:SRoot:Shoot Ratio
GRMGrowth Rate Model
CCHCompensatory Continuum Hypothesis
LRMLimiting Resource Model
DBHDiameter at Breast Height
ITCInstituto Tecnológico de Conkal.
CESVYComité Estatal de Sanidad Vegetal de Yucatán.
SEStandard Error
GLMGeneralized Linear Models
ANOVAAnalysis of Variance
AICAkaike Information Criterion
RHRelative Humidity
PPFDPhotosynthetic Photon Flux Density

References

  1. Yadav, S.K. Heavy metals toxicity in plants: An overview on the role of glutathione and phytochelatins in heavy metal stress tolerance of plants. S. Afr. J. Bot. 2010, 76, 167–179. [Google Scholar] [CrossRef]
  2. Saleem, M.H.; Ejaz, U.; Vithanage, M.; Bolan, N.; Siddique, K.H. Synthesis, characterization, and advanced sustainable applications of copper oxide nanoparticles: A review. Clean Technol. Environ. 2024, 1–26. [Google Scholar] [CrossRef]
  3. Ali, Z.; Malik, R.N.; Shinwari, Z.K.; Qadir, A. Enrichment, risk assessment, and statistical apportionment of heavy metals in tannery-affected areas. Int. J. Environ. Sci. Technol. 2015, 12, 537–550. [Google Scholar] [CrossRef]
  4. Saleem, M.H.; Ali, S.; Hussain, S.; Kamran, M.; Chattha, M.S.; Ahmad, S.; Aqeel, M.; Rizwan, M.; Aljarba, N.H.; Alkahtani, S.; et al. Flax (Linum usitatissimum L.): A potential candidate for phytoremediation? Biological and economical points of view. Plants 2020, 9, 496. [Google Scholar] [CrossRef] [PubMed]
  5. Saleem, M.H.; Ali, S.; Kamran, M.; Iqbal, N.; Azeem, M.; Javed, M.T.; Ali, Q.; Haider, M.Z.; Irshad, S.; Rizwan, M.; et al. Ethylenediaminetetraacetic acid (EDTA) mitigates the toxic effect of excessive copper concentrations on growth, gaseous exchange and chloroplast ultrastructure of Corchorus capsularis L. and improves copper accumulation capabilities. Plants 2020, 9, 756. [Google Scholar] [CrossRef] [PubMed]
  6. Miñón-Huesca, E.; González-Alcorta, M.J.; Huerta-Bravo, M.; Crespo-López, G.; Carrillo-Domínguez, S.; Casti-llo-Domínguez, R.M.; Cuca-García, J.M.; Morales-Barrera, J.E. Niveles óptimos biológico y económico de cobre dietético en pollos de engorda. Agrociencia 2006, 40, 163–170. [Google Scholar]
  7. Saleem, M.H.; Fahad, S.; Khan, S.U.; Din, M.; Ullah, A.; Sabagh, A.E.; Hossain, A.; Llanes, A.; Liu, L. Copper-induced oxidative stress, initiation of antioxidants and phytoremediation potential of flax (Linum usitatissimum L.) seedlings grown under the mixing of two different soils of China. Environ. Sci. Pollut. Res. 2020, 27, 5211–5221. [Google Scholar] [CrossRef]
  8. Ryser, P.; Emerson, P. Growth, root and leaf structure, and biomass allocation in Leucanthemum vulgare Lam. (Asteraceae) as influenced by heavy-metal-containing slag. Plant Soil 2007, 301, 315–324. [Google Scholar] [CrossRef]
  9. Northfield, T.D.; Ives, A.R. Coevolution and the effects of climate change on interacting species. PLoS Biol. 2013, 11, e1001685. [Google Scholar] [CrossRef]
  10. Lequeux, H.; Hermans, C.; Lutts, S.; Verbruggen, N. Response to copper excess in Arabidopsis thaliana: Impact on the root system architecture, hormone distribution, lignin accumulation and mineral profile. Plant Physiol. Biochem. 2010, 48, 673–682. [Google Scholar] [CrossRef]
  11. Jiang, W.; Liu, D.; Liu, X. Effects of copper on root growth, cell division, and nucleolus of Zea mays. Biol. Plant. 2001, 44, 105–109. [Google Scholar] [CrossRef]
  12. Liu, D.; Jiang, W.; Meng, Q.; Zou, J.; Gu, J.; Zeng, M. Cytogenetical and ultrastructural effects of copper on root meristem cells of Allium sativum L. Biocell 2009, 33, 25–32. [Google Scholar] [CrossRef]
  13. Dirzo, R.; Thompson, J.N. La coevolución y las enseñanzas de Darwin. Cienc. Hoy 2009, 19, 43–48. [Google Scholar]
  14. Marquis, R.J. Leaf herbivores decrease fitness of a tropical plant. Science 1984, 226, 537–539. [Google Scholar] [CrossRef]
  15. Boege, K. Influence of plant ontogeny on compensation to leaf damage. Am. J. Bot. 2005, 92, 1632–1640. [Google Scholar] [CrossRef]
  16. Ballina-Gómez, H.S.; Iriarte, V.S.; Orellana, R.; Santiago, L.S. Crecimiento, supervivencia y herbivoría de plántulas de Brosimum alicastrum (Moraceae), una especie del sotobosque neotropical. Rev. Biol. Trop. 2008, 56, 2055–2067. [Google Scholar] [CrossRef] [PubMed]
  17. Ballina-Gómez, H.S.; Iriarte, V.S.; Orellana, R.; Santiago, L.S. Compensatory growth responses to defoliation and light availability in two native Mexican woody plant species. J. Trop. Ecol. 2010, 26, 163–171. [Google Scholar] [CrossRef]
  18. Martínez, C.L.; Riquelme Virgala, M.B.; Santadino, M.V.; de Haro, A.M.; Barañao, J.J. Estudios sobre el comportamiento de forrajeo de Acromyrmex lundi Guering (HYMENOPTERA, FORMICIDAE) y su efecto sobre el crecimiento de procedencias de Eucalyptus globulus Labill. (Myrtaceae). Rev. Árvore 2015, 39, 189–198. [Google Scholar] [CrossRef]
  19. Hicks, S.; Turkington, R. Compensatory growth of three herbaceous perennial species: The effects of clipping and nutrient availability. Can. J. Bot. 2000, 78, 759–767. [Google Scholar] [CrossRef]
  20. Hilbert, D.W.; Swift, D.M.; Detling, J.K.; Dyer, M.I. Relative growth rates and the grazing optimization hypothesis. Oecologia 1981, 51, 14–18. [Google Scholar] [CrossRef]
  21. Maschinski, J.; Whitham, T.G. The continuum of plant responses to herbivory: The influence of plant association, nutrient availability, and timing. Am. Nat. 1989, 134, 1–19. [Google Scholar] [CrossRef]
  22. Wise, M.J.; Abrahamson, W.G. Beyond the compensatory continuum: Environmental resource levels and plant tolerance of herbivory. Oikos 2005, 109, 417–428. [Google Scholar] [CrossRef]
  23. Hawkes, C.V.; Sullivan, J.J. The Impact of Herbivory on Plants in Different Resource Conditions: A Meta-Analysis. Ecology 2001, 82, 2045–2058. [Google Scholar] [CrossRef]
  24. Camargo, I.D.; Tapia-López, R.; Núñez-Farfán, J. Ecotypic variation in growth responses to simulated herbivory: Trade-off between maximum relative growth rate and tolerance to defoliation in an annual plant. AoB Plants 2015, 7, plv015. [Google Scholar] [CrossRef] [PubMed]
  25. Dobarro, I. Respuestas de la Vegetación al Pastoreo: Mecanismos Relacionados Con la Defoliación en Especies Mediterrá-Neas. Ph.D. Thesis, Universidad Autónoma de Madrid, Madrid, Spain, 2009. [Google Scholar]
  26. Poorter, H. Interspecific variation in relative growth rate: On ecological causes and physiological consequences. Acta Bot. Neerl. 1989, 38, 237–250. [Google Scholar]
  27. Poorter, H. Plant growth at elevated CO2. In Encyclopedia of Global Environmental Change; Mooney, H.A., Canadell, J.G., Eds.; Wiley: Chichester, UK, 2002; pp. 489–496. [Google Scholar]
  28. Khalil Gardezi, A.; Barcelo-Quintal, I.D.; Cetina-Alcalá, V.M.; Bussy, A.L.; Pérez-Nieto, J.; Borja-Salin, M.A. Absorción de cobre y características de Leucaena leucocephala asociada con Glomus spp. y Rhizobium en suelo contaminado del Río Lerma, México. TERRA Latinoam. 2006, 24, 347–354. [Google Scholar]
  29. Lima Lins, C.E.; Cavalcante, U.M.T.; Sampaio, E.V.S.B.; Messias, A.S.; Maia, L.C. Growth of mycorrhized seedlings of Leucaena leucocephala (Lam.) de Wit. in a copper contaminated soil. Appl. Soil Ecol. 2006, 31, 181–185. [Google Scholar] [CrossRef]
  30. Grijalva, J.; Ramos, R.; Vera, A. Pasturas Para Sistemas Silvopastoriles: Alternativa Para el Desarrollo Sostenible de la Ganadería en la Amazonía Baja de Ecuador; Boletín Técnico Nº 156; Programa Nacional de Forestería del INIAP: Quito, Ecuador, 2011. [Google Scholar]
  31. Villar, R.; Marañón, T.; Quero, J.L.; Panadero, P.; Arenas, F.; Lambers, H. Variation in relative growth rate of 20 Aegilops species (Poaceae) in the field: The importance of net assimilation rate or specific leaf area depends on the time scale. Plant Soil 2005, 272, 11–27. [Google Scholar] [CrossRef]
  32. Arenas, A.D.; Marcó, L.M.; Torres, G. Evaluación de la planta Lemna minor como biorremediadora de aguas contaminadas con mercurio. Av. Cienc. Ing. 2011, 2, 1–11. [Google Scholar]
  33. Varnagiryte-Kabašinskiene, I.; Araminiene, V.; Stakenas, V. Effects of artificial defoliation and simulated insect damage on the growth of Betula pendula saplings. iForest 2015, 9, 95–100. [Google Scholar] [CrossRef]
  34. Casanova, L. Caracterización de la Vegetación Secundaria del Área Experimental Que se Ubica al Noreste del Campus Uni-versitario de la Facultad de Medicina Veterinaria y Zootecnia. Bachelor’s Thesis, Universidad Autónoma de Yucatán, Mérida, Mexico, 2000. [Google Scholar]
  35. Flores, J.S.; Durán, R.; Ortiz, D.J. Comunidades vegetales terrestres. In Biodiversidad y Desarrollo Humano en Yucatán; Durán, R., Méndez, M., Eds.; CICY-PPD-FMAM: Mérida, México, 2010; pp. 125–129. [Google Scholar]
  36. Flores, J.S.; Espejel, I. Tipos de vegetación de la península de Yucatán. Etnoflora Yucatanense 1994, 3, 1–35. [Google Scholar]
  37. White, D.A.; Hood, C.S. Vegetation patterns and environmental gradients in tropical dry forest of the northern Yucatan Peninsula. J. Veg. Sci. 2004, 15, 151–160. [Google Scholar] [CrossRef]
  38. Pennington, T.D.; Sarukhán, J. Árboles tropicales de México. In Manual Para la Identificación de las Principales Especies, 3rd ed.; Universidad Nacional Autónoma de México-Fondo de Cultura Económica: Mexico City, Mexico, 2005. [Google Scholar]
  39. Gómez-Castro, H.; Pinto-Ruiz, R.; Guevara-Hernández, F.; González-Reyna, A. Estimaciones de biomasa aérea y carbono almacenado en Gliricidia sepium (Lam.) y Leucaena leucocephala (Jacq.) y su aplicación en sistemas silvopastoriles. ITEA 2010, 106, 256–270. [Google Scholar]
  40. Borges-Gómez, L.; Moo-Kauil, C.; Ruíz-Novelo, J.; Osalde-Balam, M.; González-Valencia, C.; Yam-Chimal, C.; Can-Puc, F. Suelos destinados a la producción de chile habanero en Yucatán: Características físicas y químicas predominantes. Agrociencia 2014, 48, 347–359. [Google Scholar]
  41. Poorter, H.; Garnier, E. Plant growth analysis: An evaluation of experimental design and computational methods. J. Exp. Bot. 1996, 47, 1343–1351. [Google Scholar] [CrossRef]
  42. Johnson, M.T.; Bertrand, J.A.; Turcotte, M.M. Precision and accuracy in quantifying herbivory. Ecol. Entomol. 2016, 41, 112–121. [Google Scholar] [CrossRef]
  43. Rasband, W.S. ImageJ; U.S. National Institutes of Health: Bethesda, MD, USA, 2012; Available online: https://imagej.net/ (accessed on 25 December 2024).
  44. McCullagh, P.; Nelder, J.A. Generalized Linear Models, 2nd ed.; Chapman & Hall: London, UK, 1989. [Google Scholar] [CrossRef]
  45. IBM Corp. IBM SPSS Statistics for Windows, Version 22.0; IBM Corp.: Armonk, NY, USA, 2013. [Google Scholar]
  46. Arbuckle, J.L. IBM SPSS Amos 19 User’s Guide; Amos Development Corporation: Crawfordsville, FL, USA, 2012. [Google Scholar]
  47. Morales, J.M.L.; Sepúlveda-Jiménez, G. El daño por oxidación causado por cobre y la respuesta antioxidante de las plantas. Interciencia 2012, 37, 805–811. [Google Scholar]
  48. Barceló-Quintal, I.D.; García-Alamilla, P.; Gómez-González, M.A. Fitorremediación de suelos contaminados con metales pesados utilizando Leucaena leucocephala. Rev. Mex. Ing. Quím. 2016, 15, 431–440. [Google Scholar]
  49. Pires-Bomfim, P.M.C.; Demarco, D.; De Marco, P., Jr. Heavy metal accumulation in Leucaena leucocephala: Implications for phytoremediation in tropical soils. Environ. Sci. Pollut. Res. 2023, 30, 43210–43221. [Google Scholar] [CrossRef]
  50. Calle, Z.; Murgueitio, E.; Chará, J. Integración de árboles en sistemas ganaderos para la rehabilitación ecológica. Agrofor. Am. 2011, 48, 12–19. [Google Scholar]
  51. Amaya-Martin, S.M.; Ballina-Gomez, H.S.; Alvarado-López, C.; Ruiz-Sánchez, E.; Gil-Cardeza, M.; Azcorra-Perera, G. Cadmium tolerance and resistance to damage by Bemisia tabaci induced by a consortium of arbuscular mycorrhizal fungi in Solanum lycopersicum L. Trop. Subtrop. Agroecosyst. 2025, 28, 1–12. [Google Scholar] [CrossRef]
  52. Nanthavong, K.; Sampanpanish, P. Effect of NTA and EDTA on arsenic uptake from contaminated soil by Mimosa pudica. Mod. Appl. Sci. 2015, 9, 280–291. [Google Scholar] [CrossRef]
  53. Marozzi, M.; Villalba, A.; Polla, W.; Hadad, H.; Devercelli, M. Cambios en la morfología y en la tasa de crecimiento de Pistia stratiotes (Araceae) asociados a la presencia de plomo. Cienc. Agrar. 2003, 2, 1–2. [Google Scholar] [CrossRef]
  54. Kabata-Pendias, A. Trace Elements in Soils and Plants, 3rd ed.; CRC Press: Boca Raton, FL, USA, 2000. [Google Scholar] [CrossRef]
  55. Freeman, J.L.; Lindblom, S.D.; Quinn, C.F.; Fakra, S.; Marcus, M.A.; Pilon-Smits, E.A.H. Selenium accumulation protects plants from herbivory by Orthoptera via toxicity and deterrence. New Phytol. 2007, 175, 490–500. [Google Scholar] [CrossRef] [PubMed]
  56. Wise, M.J.; Mudrak, E.L. Revisiting the Limiting Resource Model: Context-dependent plant tolerance to herbivory. Ecol. Lett. 2023, 26, 512–523. [Google Scholar]
  57. Wise, M.J.; Abrahamson, W.G. Effects of resource availability on tolerance of herbivory: A review and assessment of three opposing models. Am. Nat. 2007, 169, 443–454. [Google Scholar] [CrossRef]
  58. Banta, J.A.; Stevens, M.H.H.; Pigliucci, M. A comprehensive test of the limiting resource framework applied to plant tolerance to apical meristem damage. Oikos 2010, 119, 359–369. [Google Scholar] [CrossRef]
  59. March, P.J.; Wise, M.J.; Abrahamson, W.G. The effect of resource stress on goldenrod’s tolerance of folivory depends more on the identity of the stress than on the severity of the stress. Int. J. Mod. Bot. 2013, 3, 15–25. [Google Scholar]
  60. Wise, M.J.; Abrahamson, W.G. Applying the limiting resource model to plant tolerance of apical meristem damage. Am. Nat. 2008, 172, 635–647. [Google Scholar] [CrossRef]
  61. Houghton, J.; Thompson, K.; Rees, M. Does seed mass drive the differences in relative growth rate between growth forms? Proc. R. Soc. B 2013, 280, 20130921. [Google Scholar] [CrossRef]
  62. Shibuya, T.; Shimizu, K.; Nishioka, N. Growth responses of Arabidopsis thaliana to salinity stress: The role of ion homeostasis. Plant Cell Physiol. 2024, 65, 387–398. [Google Scholar]
  63. Matsuda, R.; Suzuki, K.; Nakano, A. Light availability and photosynthetic acclimation in understory plants. Front. Plant Sci. 2023, 14, 1123456. [Google Scholar]
  64. van Staalduinen, M.A.; Anten, N.P.R. Differences in the compensatory growth of two co-occurring grass species in relation to water availability. Oecologia 2005, 146, 190–199. [Google Scholar] [CrossRef] [PubMed]
  65. Carrillo-Herrera, E.F.; Dzib-Ek, S.A.; Ballina-Gómez, H.S. Influence of herbivory and gap-openness on whole-plant growth of Brosimum alicastrum (Moraceae). Acta Biol. Colomb. 2021, 26, 186–195. [Google Scholar] [CrossRef]
  66. Eichholtzer, J.; Ballina-Gómez, H.S.; Gómez-Tec, K.; Medina-Dzul, K. Arbuscular mycorrhizal fungi influence whitefly abundance by modifying habanero pepper tolerance to herbivory. Arthropod Plant Interact. 2021, 15, 861–874. [Google Scholar] [CrossRef]
  67. Baraloto, C.; Bonal, D.; Goldberg, D.E. Differential seedling growth responses to soil resource availability among nine neotropical tree species. J. Trop. Ecol. 2006, 22, 487–497. [Google Scholar] [CrossRef]
  68. Gandhi, S.; Thangavel, M.; Kumar, R.S. Morpho-physiological responses of Brassica juncea to heavy metal stress: A comparative study. Environ. Exp. Bot. 2020, 178, 104123. [Google Scholar]
  69. Ali, A.; Khan, B.; Sajid, M. Heavy metal accumulation and tolerance mechanisms in hyperaccumulator plants: A review. Environ. Res. 2024, 215, 114312. [Google Scholar]
  70. Reich, P.B.; Walters, M.B.; Ellsworth, D.S. Leaf life-span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol. Monogr. 1992, 62, 365–392. [Google Scholar] [CrossRef]
  71. Huante, P.; Rincón, E.; Acosta, I. Nutrient availability and growth rate of 34 woody species from a tropical deciduous forest in Mexico. Funct. Ecol. 1995, 9, 849–858. [Google Scholar] [CrossRef]
  72. Cornelissen, J.H.C.; Castro Diez, P.; Hunt, R. Seedling growth, allocation and leaf attributes in a wide range of woody plant species and types. J. Ecol. 1996, 84, 755–765. [Google Scholar] [CrossRef]
  73. Antúnez, I.; Retamosa, E.C.; Villar, R. Relative growth rate in phylogenetically related deciduous and evergreen woody species. Oecologia 2001, 128, 172–180. [Google Scholar] [CrossRef] [PubMed]
  74. Villar, R.; López-Iglesias, B.; Ruiz-Benito, P.; Zavala, M.A.; De la Riva, E.G. Crecimiento de plántulas y árboles de seis especies de Quercus. Ecosistemas 2014, 23, 64–72. [Google Scholar]
  75. Pérez-Garrido, C.; Fernández-Díaz, L.; Pina, C.M.; Prieto, M. In situ AFM observations of the interaction between calcite (1014) surfaces and Cd-bearing aqueous solutions. Surf. Sci. 2007, 601, 5499–5509. [Google Scholar] [CrossRef]
  76. Luna, C.M.; González, C.A.; Trippi, V.S. Oxidative damage caused by an excess of copper in oat leaves. Plant Cell Physiol. 1994, 35, 11–15. [Google Scholar]
  77. Burzyński, M.; Klobus, G. Changes of photosynthetic parameters in cucumber leaves under Cu, Cd and Pb stress. Photosynthetica 2004, 42, 505–510. [Google Scholar] [CrossRef]
  78. Khatun, S.; Ali, M.B.; Hahn, E.J.; Paek, K.Y. Copper toxicity in Withania somnifera: Growth and antioxidant enzymes responses of in vitro grown plants. Environ. Exp. Bot. 2008, 64, 279–285. [Google Scholar] [CrossRef]
  79. Russo, M.; Sgherri, C.; Izzo, R.; Navari-Izzo, F. Brassica napus subjected to copper excess: Phospholipases C and D and glutathione system in signaling. Environ. Exp. Bot. 2008, 62, 238–246. [Google Scholar] [CrossRef]
  80. Poorter, H.; Niklas, K.J.; Reich, P.B.; Oleksyn, J.; Poot, P.; Mommer, L. Biomass allocation to leaves, stems and roots: Meta-analyses of interspecific variation and environmental control. New Phytol. 2012, 193, 30–50. [Google Scholar] [CrossRef]
  81. Huu Thanh, N.; Le Ha, T.T.; Viet Ha, C.; Duc Hung, N.; Quoc Hung, P.; Kurosawa, K.; Egashira, K. Uptake of Pb, Zn and Cu by roots and shoots of fast growing plants grown in contaminated soil in Vietnam. J. Soil Sci. Environ. Manag. 2013, 4, 108–115. [Google Scholar] [CrossRef]
  82. Yang, X.; Li, Y.; Wang, Z. Biomass reallocation in plants under heavy metal stress: A meta-analysis. Environ. Exp. Bot. 2024, 218, 105612. [Google Scholar]
  83. Hackett, S.C.; Karley, A.J.; Bennett, A.E. Unpredicted impacts of insect endosymbionts on interactions between soil organisms, plants and aphids. Proc. R. Soc. B 2013, 280, 20131275. [Google Scholar] [CrossRef] [PubMed]
  84. Poorter, H.; van der Werf, A. Is inherent variation in RGR determined by LAR at low irradiance and by NAR at high irradiance? A review of herbaceous species. In Inherent Variation in Plant Growth; Lambers, H., Poorter, H., Van Vuuren, M.M.I., Eds.; Backhuys: Leiden, The Netherlands, 1998; pp. 309–336. [Google Scholar]
  85. Barchuk, A.; Iglesias, M.R.; Oviedo, C. Rebrote basal de Aspidosperma quebracho-blanco en estado de plántula: Mecanismo de persistencia en el Chaco Árido. Ecol. Austral 2006, 16, 197–205. [Google Scholar]
Ijpb 16 00076 g001
Figure 1. Effect of copper and herbivory of locust (Sch. piceifrons) on the growth, morphological and physiological components of RGRB in L. Leucocephala seedlings. (A) RGRB, (B) RGRLA, (C) Leaf production rate, (D) LAR, (E) SLA and (F) NAR.
Figure 1. Effect of copper and herbivory of locust (Sch. piceifrons) on the growth, morphological and physiological components of RGRB in L. Leucocephala seedlings. (A) RGRB, (B) RGRLA, (C) Leaf production rate, (D) LAR, (E) SLA and (F) NAR.
Ijpb 16 00076 g001
Ijpb 16 00076 g002
Figure 2. Logistic regression to estimate survival probability as a Cu treatment function and time in seedlings of L. leucocephala for 25 days.
Figure 2. Logistic regression to estimate survival probability as a Cu treatment function and time in seedlings of L. leucocephala for 25 days.
Ijpb 16 00076 g002
Ijpb 16 00076 g003
Figure 3. Path analysis of causal influences of morphological (LAR, SLA, and LWR) and physiological (NAR) components on RGRB of L. leucocephala seedlings. Numbers on arrows are standardized path coefficients (equivalent to correlation coefficients). *** Indicate significant standardized path coefficients (p > 0.0001). Circles indicate error terms (e1–e2). Model fitted the data: χ2 = 0.300, probability level = 0.861, AIC = 36.300.
Figure 3. Path analysis of causal influences of morphological (LAR, SLA, and LWR) and physiological (NAR) components on RGRB of L. leucocephala seedlings. Numbers on arrows are standardized path coefficients (equivalent to correlation coefficients). *** Indicate significant standardized path coefficients (p > 0.0001). Circles indicate error terms (e1–e2). Model fitted the data: χ2 = 0.300, probability level = 0.861, AIC = 36.300.
Ijpb 16 00076 g003
Ijpb 16 00076 g004
Figure 4. Effect of copper and herbivory of locust (Sch. piceifrons) on the mass allocation to (A) leaves (LWR), (B) stems (SWR), (C) roots (RWR) and (D) ratio root:shoot (R:S) in L. leucocephala seedlings.
Figure 4. Effect of copper and herbivory of locust (Sch. piceifrons) on the mass allocation to (A) leaves (LWR), (B) stems (SWR), (C) roots (RWR) and (D) ratio root:shoot (R:S) in L. leucocephala seedlings.
Ijpb 16 00076 g004
Table 1. Effect of copper and herbivory on plant growth and morphological components of the RGRB (mean ± SE) in L. leucocephala seedlings.
Table 1. Effect of copper and herbivory on plant growth and morphological components of the RGRB (mean ± SE) in L. leucocephala seedlings.
EffectRGRB
(g g−1 d−1)		χ2RGRLA
(cm2 cm−2 d−1)		χ2LPR (no.)χ2LAR
(cm2 g−1)		χ2SLA
(cm2 g−1)		χ2
Inter-subjects
Copper treatment 1.67 ns 0.44 ns 1.35 ns 0.27 ns 7.37 *
Control0.0157 ± 0.0079 a −0.0534 ± 0.0097 a −0.1585 ± 0.1184 a 241.48 ± 15.15 a 848.96 ± 74.01 a
Low copper0.0042 ± 0.0090 a −0.0623 ± 0.0107 a −0.3063 ± 0.1803 a 227.05 ± 18.67 a 772.51 ± 93.94 a
High copper0.0048 ± 0.0069 a −0.0518 ± 0.0133 a −0.2243 ± 0.1979 a 248.48 ± 24.92 a 1859.2 ± 605.3 b
Intra-subjects
Herbivory treatment 1.03 ns 0.015 ns 8.49 ** 0.36 ns 7.4 *
Control0.0150 ± 0.0077 a −0.0503 ± 0.0085 a 0.0081 ± 0.1610 a 231.90 ± 14.89 a 794.97 ± 81.11 a
Herbivory0.0035 ± 0.0055 a −0.0609 ± 0.0091 a −0.4357 ± 0.0703 b 244.88 ± 15.68 a 1379.6 ± 331.2 b
Copper × Herbivory 1.77 ns 20.24 *** 0.68 ns 0.52 ns 9.48 *
Note. Different letters indicate significant differences (Bonferroni < 0.05). * p < 0.05. ** p < 0.01. *** p < 0.001. ns, not significant.
Table 2. Results of a logistic regression to predict survival of seedlings of Leucaena leucocephala.
Table 2. Results of a logistic regression to predict survival of seedlings of Leucaena leucocephala.
FactorExp (β)βStandard ErrorConfidence Intervals 95%
Lower Upper		χ2 Walddfp Value
Copper treatment 86.32<0.0001
Cu0.543−0.6100.1320.4200.70321.51<0.0001
Cu+0.288−1.2440.1810.2220.37586.11<0.0001
Time (Days)0.849−0.1630.0090.8350.864349.61<0.0001
Note. We included time and copper treatments as continuous and categorical variables. In each variable we showed beta parameters estimates (β ± standard error), significance level (χ2 Wald), Exp (β), confidence intervals (95%), and its degrees of freedom (df).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Amaya-Martín, S.M.; Ballina-Gómez, H.S.; Ruíz-Sánchez, E.; Azcorra-Perera, G.J.; Ruiz-Santiago, R.R.; Pierre, J.F. Interactive Effect of Copper and Herbivory on the Whole-Plant Growth of Leucaena leucocephala. Int. J. Plant Biol. 2025, 16, 76. https://doi.org/10.3390/ijpb16030076

AMA Style

Amaya-Martín SM, Ballina-Gómez HS, Ruíz-Sánchez E, Azcorra-Perera GJ, Ruiz-Santiago RR, Pierre JF. Interactive Effect of Copper and Herbivory on the Whole-Plant Growth of Leucaena leucocephala. International Journal of Plant Biology. 2025; 16(3):76. https://doi.org/10.3390/ijpb16030076

Chicago/Turabian Style

Amaya-Martín, Shirley Margarita, Horacio Salomón Ballina-Gómez, Esaú Ruíz-Sánchez, Gabriel Jesús Azcorra-Perera, Roberto Rafael Ruiz-Santiago, and Jacques Fils Pierre. 2025. "Interactive Effect of Copper and Herbivory on the Whole-Plant Growth of Leucaena leucocephala" International Journal of Plant Biology 16, no. 3: 76. https://doi.org/10.3390/ijpb16030076

APA Style

Amaya-Martín, S. M., Ballina-Gómez, H. S., Ruíz-Sánchez, E., Azcorra-Perera, G. J., Ruiz-Santiago, R. R., & Pierre, J. F. (2025). Interactive Effect of Copper and Herbivory on the Whole-Plant Growth of Leucaena leucocephala. International Journal of Plant Biology, 16(3), 76. https://doi.org/10.3390/ijpb16030076

Article Metrics

Back to TopTop