Cattle Grazing Impacts on Shoot and Root Characteristics of Urochloa decumbens (Stapf) R. Webster and Axonopus compressus (Sw.) P. Beauv. in Tropical Pastures of Malaysia
Majid Ajorlo
1
(
University of Zabol
)
Ramdzani Abdullah
2
(
Department of Environmental Management, Faculty of Environmental Studies, University Putra Malaysia
)
Mahboubeh Ebrahimian
3
(
Research Institute for Hamoun International Wetland, University of Zabol
)
کلید واژه: Root morphology, Herbage Mass, Regrowth Rate, Tiller Density, Root Distribution,
چکیده مقاله :
This study aimed to assess the responses of Signal grass (Urochloa decumbens) and Carpet grass (Axonopus compressus) shoot and root systems to cattle grazing. Two sites with different grazing strategies were selected in pastures of Selangor state, Malaysia in 2016: one site was dominated by Signal grass and grazed with moderate intensity for long-term (LMG, 2.7 animal unit/ha/yr) and the second site was dominated by Carpet grass and grazed with heavy intensity for short-term (SHG, 5 animal unit/ha/yr). Shoot growth was similarly assessed for both species by measuring herbage mass, plant height, regrowth rate, tiller density and litter biomass four times at the end of the growing periods in both grazed and ungrazed (control) sites. Root samples of species were taken from the center of the individual plants to a depth of 30 cm and analyzed for root length, diameter, surface area, volume and mass using WinRhizo Root Scanner. The relationship between root distribution parameters and soil depth was examined using least square curve fitting. The LMG strategy increased herbage production (g DM/m2), regrowth rate (g DM/d/m2) and tiller density of Signal grass by 19, 26 and 69%, respectively, compared with the ungrazed site (P<0.05). For this grazing strategy, the mean root length (-18%) decreased (P<0.05), but root mass (+46%) increased (P<0.05). In SHG strategy, herbage production and regrowth rate of Carpet grass were unaffected by grazing but tiller density was 147% increased than the ungrazed site. This grazing strategy decreased mean root length by 38%, but increased root diameter and volume of Carpet grass by 22 and 59%, respectively, and had no effect on root mass. It was concluded that short-term heavy grazing had negative impacts on the root characteristics of studied species than long-term moderate grazing. Therefore, long-term moderate grazing by cattle is recommended for the study area.
چکیده انگلیسی :
تأثیر چرای گاو در ویژگیهای اندامهای هوایی و ریشه Urochloa decumbens (Stapf) R. Webster و Axonopus compressus (Sw.) P. Beauv. در چراگاههای استوایی مالزی
Abstract:
This study aimed to quantitatively assess the responses of Signal grass (Urochloa decumbens (Stapf) R. Webster) and Carpet grass (Axonopus compressus (Sw.) P. Beauv.) shoot and root systems to long-term moderate grazing (LMG, 2.7 animal unit/ha/yr) and short-term heavy grazing (SHG, 5 animal unit/ha/yr) strategies in tropical pastures of Selangor state, Malaysia in 2016. Shoot growth was assessed by measuring herbage mass, plant height, regrowth rate, tiller density and litter biomass four times at the end of the growing periods. Root samples were taken from the center of individual plant using soil coring approach by direct extracting of cores to a depth of 30 and analyzed for length, diameter, surface area, volume and mass with WinRhizo Root Scanner. The relationship between root distribution parameters with soil depth for individual root cores were examined by least square curve fitting. The LMG strategy increased herbage production (g DM/m2), regrowth rate (g DM/d/m2) and tiller density of Signal grass by 19, 26 and 69%, respectively (P < 0.05). This grazing strategy decreased (P < 0.05) mean root length (-18%) but increased (P < 0.05) root mass (+46%) whereas root diameter, surface area and volume were unaffected (P > 0.05). In SHG strategy, herbage production and regrowth rate of Carpet grass were unaffected (P > 0.05) by grazing but tiller density increased by 147%. This grazing strategy decreased (P < 0.05) mean root length by 38% but increased (P < 0.05) root diameter and volume of Carpet grass by 22 and 59%, respectively and had no effect (P > 0.05) on root mass. Short-term heavy grazing had greater impact on root characteristics of the studied species than the long-term moderate grazing.
Keywords: Herbage Mass; Regrowth Rate; Tiller Density; Root Morphology; Root Distribution
1. Introduction
In Malaysia, grazing lands consist of grazing reserves (communal grazing land) and commercial improved pastures. Grazing reserves are natural grassland with low productivity and poor forage quality. Carpet grass (Axonopus compressus) is highly dominated species in these ecosystems. These grazing lands are used for communal livestock ranching by smallholders. Heavy stocking rate is a common problem in the majority of natural grassland (Suhartini et al., 2020). Improved pastures are used for commercial livestock ranching by governmental and private sectors. In spite of communal grazing lands, improved pastures are managed intensively with moderate stocking rate. Signal grass (Urochloa decumbens) is one of the introduced grass plants which is largely used to establish improved pastures in Malaysia (Ajorlo, 2010).
Tropical pastures grow for 12 months in a year due to permanent favorable environmental conditions and grass plants complete their growth cycle in 4 to 6 weeks. These pastures are subject to periodic grazing with varying intensity and frequency (Ajorlo, 2010). Grazing can affect both above- and below-ground phytomass of plants directly or indirectly through defoliation, treading, and waste deposition (Bilotta et al., 2007). Chen et al., (2006) observed that grazing affects the below-ground more than it does the above-ground. However, the response of grass plants to grazing can vary within a species and between species (Dawson et al., 2000).
The extent of change in pasture plants is greatly influenced by intensity, frequency, timing and period of grazing. In addition, animal species, climatic and edaphic conditions influence the response of pastures to grazing (Deutsch et al., 2010; Sulistijo et al., 2021). Under heavy grazing intensity, for example, herbage production can decrease and the vegetation structure change to a high density of smaller tillers (Dawson et al., 2000). Herbage production, plant height, growth rate, tiller density and litter biomass provide a good set of vegetal indicators for determining the response of shoots to grazing strategy (Holland et al., 2008; Shakhane et al., 2013).
Plant root systems play pivotal role in nutrient cycle and energy flow of pasture and grassland ecosystems. It is important to understand how root response to grazing and what it means to pasture health (Peng et al., 2022). Root systems respond to grazing with both architectural and morphological changes, which may affect root demography and/or physiology (Arredondo and Johnson, 1998). Grazing can reduce the rate of root growth (Arredondo and Johnson, 1999) or even result in the complete cessation of root growth and function (Richards, 1984). The reduction in root growth following defoliation is in response to reduced photosynthesis and carbon assimilation, which ensures that leaves can regrow to support the root mass (Hendrickson and Olson, 2006; Ajorlo et al., 2014). The root architecture and morphological response to grazing is also influenced by soil physical and chemical properties, plant physiological condition, stage of development and carbohydrate allocation patterns (Hendrickson and Olson, 2006).
Signal grass (Urochloa decumbens (Stapf) R. Webster) is a fast-growing perennial C4 grass that produces both erect shoots and stolon. It has a very dense root system in the upper soil layers with more than 80% of root mass within the first 30 cm of the soil profile (Guenni et al., 2002; Ajorlo, 2010). It has been widely used for the establishment of improved commercial pastures in the tropics. Carpet grass (Axonopus compressus (Sw.) P. Beauv.) is a C4 stoloniferous perennial grass that grows in acidic (pH 4.0-7.0) and low fertility soils to a maximum height of about 20-50 cm. It is a dominant grass in communal native grasslands in tropical regions (Smith and Valenzuela, 2002; Ajorlo, 2010). Both species are dependent on grazing disturbance, or anthropogenic interference, for their maintenance.
Grazing affects below-ground part of plants more than it does to above-ground processes (Chen et al., 2006). Although knowledge of plant roots characteristics is essential to understanding pastures healthiness and plant uptake of soil water and nutrients in grassland, most published literature reported plants above-ground response to animal grazing and few such studies have been conducted to quantify root responses to grazing (Ajorlo, 2010). One of the reasons behind this, is the study of root distribution are tedious and time consuming. Therefore, root system of grassland ecosystem is one of the least studied components. It is estimated that less than 10 % of the studies on pastures and rangeland have evaluated the below-ground biomass production (Oliveira et al., 2000). There is a general agreement among scientists about the importance of both shoot and root studies when evaluating the effect of defoliation on grasses (for example, Greenwood and Hutchinson, 1998; Dawson et al., 2000; Mousel et al., 2004; Chen et al., 2006; Lodge and Murphy, 2006Wang et al., 2023). However, most published studies report only on the above-ground response and studies that examine both above- and below-ground response are limited (Greenwood and Hutchinson, 1998; Dawson et al., 2000; Oliveira et al., 2000; Chen et al., 2006). This study perhaps is among the first studies which quantified the influence of grazing management strategies on distribution and morphology of roots in tropical pastures of Malaysia. Therefore, we conducted a study to quantify the responses of both shoot growth and root morphology and distribution characteristics of Signal grass and Carpet grass to long-term moderate and short-term heavy grazing strategies in tropical pastures with the ultimate goal of understanding the effect of grazing on the health of these grasslands. In this study, we tested the hypothesis that moderated grazing would improve pasture plants shoot and root, whereas heavy grazing would impair them.
2. Materials and Method
2.1 Study site
This study was conducted at the University Putra Malaysia Livestock Section (2° 58' North and 101° 43' East), about 20 km south of Kuala Lumpur, Malaysia. Two sites with different grazing strategies were selected: one dominated largely by U. decumbens and grazed with moderate intensity for long-term (LMG) and the second dominated mainly by A. compressus and grazed with heavy intensity for short-term (SHG). The area has a humid tropical climate with mean annual rainfall of 2,471 mm and mean annual temperature of 24.5°C. The soil type was classified as Typic Hapludox (Munchong series) according to USDA classification (Soil Survey Staff, 2008) representing the Oxisols order with > 35% clay at the study sites. The soils of the sites were generally well drained.
2.2 Experimental design and grazing treatments
One site has been grazed with 2.7 animal units (AU’s)/ha/year (long-term grazing, LMG) and another site has been grazed with 5 AU’s/ha/year (short-term grazing, SHG) for 2 years. Therefore, the treatments were no grazing (control) by cattle and grazing at moderate stocking density and heavy stocking density in a rotational grazing system throughout the year.
2.3 Shoot measurements
A set of four, 10-m equally-spaced transects were established spaced 100 m apart in each plot at the LMG site. Furthermore, two 10-m transects spaced 20 m apart were established in each plot at the SHG site. Length and the numbers of transect were determined according to canopy cover percent, plant density and vegetation distribution pattern (Gillison, 2006). An exclosure cage technique was used to protect pasture plants in the grazed treatments (Mannetje, 1978). For this purpose, one quadrat (0.25 m2) with exclosure cage was randomly placed in each transect.
Immediately after cattle removal from the paddocks, residual of ungrazed vegetation of an area of the same size to quadrat was clipped at ground level (Martinez and Zinck, 2004) and the grass plants were allowed to grow undisturbed under the protection cages. Both sites were sampled for four times every six weeks in the SHG site and eight weeks intervals at the LMG site. These frequencies were defined by the growth cycle of tropical grass plants, which is longer for native tropical species than introduce grass species. All transects and exclosure cages were moved to new locations and reestablished randomly after each sampling event, respectively.
Before harvesting, we measured average tiller height using a pasture ruler (MLA, Australia) and counted tiller number. Standing and fallen plant materials that has senesced in the current growing period were collected as litter biomass. Plant materials that were produced in the current growing period and has senesced were considered litter in this study. All biomass was oven-dried and weighed. Pasture regrowth rate was expressed as the change in live biomass (DM) per unit of time (g DM/m/day) and calculated using equation 1 (Bluett et al., 1998).
(1) |
Where ∆yf is dry matter biomass (g DM m-2 day-1) after regrowth, and ∆t is number of days between harvests.
2.4. Root measurements
Roots were sampled by extracting soil cores, directly in the center of the plants, using a manually driven single root auger (Eijkelkamp Agrisearch Equipment) with an 8-cm diameter bore to a depth of 30 cm (Oliveira et al., 2000; Mousel et al., 2005). Soil cores were randomly extracted in each quadrat, and were cut into three, 10-cm segments. Individual segments were gently hand-washed with tap water to remove soil materials over a 0.20 mm sieve to ensure that fine roots were retained (Mathew et al., 1991; Lodge and Murphy, 2006).
Root samples were then placed on the tray of a root scanner (WinRhizo, Regent Instruments Inc., Quebec, Canada) containing distilled water to a depth of 3 cm. A digitized image of the entire root system of each segment was obtained with a resolution of 400 dots per inch (dpi). Each image was analyzed for root length (cm), surface area (cm2), average diameter (mm) and volume (cm3). Finally, roots were oven-dried at 65 ºC to determine mass (Mousel et al., 2005). Root length density (RLD), specific root length (SRL), root mass density (RMD), surface area density (SAD), and root volume density (RVD) were calculated for each 10-cm soil core segment.
2.5 Data analysis
All variables of shoot characteristics were averaged across the date of sampling to produce a single estimate and eliminate that factor from statistical analyses. Assumptions of normality and homogeneity of variance were checked and variables with non-normal distribution were log-transformed as appropriate. For log-transformed variables, the mean of the untransformed data was used to express central tendency, and the standard error derived from log-transformed data was used to express precision. Multivariate analysis of variance (MANOVA) using the general linear model (GLM) procedure was applied to analyze shoot data. Root data was analyzed with repeated measure analysis of variance (RM-ANOVA) in SPSS software (IBM SPSS Statistics, Version 25.0). Differences were assessed at the significance level of P < 0.05.
The relationship between root distribution parameters including root length density, root surface area density, root volume density and root mass density with soil depth for individual cores were examined by least square curve fitting. Five curvilinear functions, i.e., linear, logarithmic, power and exponential were compared.
3. Results
3.1 Shoot growth
Herbage production (g DM/m2) of Signal grass was positively affected (P ≤ 0.05) by long-term moderate grazing (LMG), but Carpet grass was unaffected (P > 0.05) by short-term heavy grazing (SHG). Mean pasture height (cm) was not affected by both grazing treatments (P > 0.05). Only regrowth rate of Signal grass (g DM/m2/d) was affected (P < 0.05) by the LMG treatment. Reproductive and vegetative tiller densities (tillers/m2) were significantly higher (P < 0.05) in the LMG and SHG pastures compared to the grazing exclosures. Both LMG and SHG treatments caused a significant decrease (P < 0.05) in litter biomass of grass plants (Table 1).
Table 1 Changes of shoot growth parameters of the studied grass species in response to cattle grazing in tropical pastures of Malaysia
Shoot variables | Signal grass |
| Carpet grass | ||||||||
Moderate grazing | Grazing exclosure | SE | F | P |
| Heavy grazing | Grazing exclosure | SE | F | P | |
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Herbage production (g DM/m2) | 160.23a | 132.35b | 19.23 | 2.10 | 0.05 |
| 134.70a | 129.88a | 17.72 | 0.074 | 0.78 |
Pasture height (cm) | 35.41a | 34.84a | 3.72 | 0.024 | 0.2 |
| 14.11a | 16.50a | 2.93 | 2.24 | 0.14 |
Regrowth rate (g DM/m2/d) | 3.23a | 2.47b | 0.316 | 5.81 | 0.02 |
| 2.58a | 2.41a | 0.327 | 0.025 | 0.61 |
Reproductive tiller (tillers/m2) | 3.98a | 2.48b | 0.491 | 9.42 | 0.003 |
| 75.13a | 5.18b | 9.29 | 56.58 | 0.00 |
Vegetative tiller (tillers/m2) | 12.30a | 6.12b | 0.070 | 10.35 | 0.002 |
| 21.45a | 9.25b | 3.05 | 16.01 | 0.00 |
Tiller density (tiller/m2) | 70.93a | 34.56b | 0.069 | 11.85 | 0.001 |
| 386.64a | 57.79b | 46.76 | 49.36 | 0.00 |
Litter biomass (g/m2) | 10.99a | 22.65b | 0.102 | 3.81 | 0.046 |
| 10.97a | 17.75b | 3.40 | 3.95 | 0.048 |
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SE: standard error
Means in with unlike letters were significantly different at P < 0.05.
3.2 Root characteristics
Long term moderate grazing (LMG) strategy resulted in smaller (P ≤ 0.05) root length, RLD and SRL but greater (P < 0.05) root mass and RMD in Signal grass. The interaction between grazing treatment and soil depths were not caused (P > 0.05) more decline of root length and RLD in the ungrazed than the grazed treatment. Also, the interaction was not caused significant decline in root mass and RMD in the grazed pasture (P > 0.05). A significant decrease of SRL was observed in moderately grazed Signal grass and at the interaction between soil depth and treatment (P < 0.05). Root diameter, volume and RVD of Signal grass were not significantly affected by LMG (P > 0.05) (Tables 2).
Short term Heavy grazing (SHG) strategy resulted significantly smaller root length and RLD, but significantly greater root diameter, volume and RVD in Carpet grass (P < 0.05). The interaction between grazing treatment and soil depths were not caused significant changes (P > 0.05) in root length, root mass and RMD in the grazed pasture of Carpet grass compared with the ungrazed pasture. Root diameter, surface area, volume, and subsequently SAD and RVD were significantly affected by the interaction between grazing and soil depths (P < 0.05) (Tables 3).
Table 2. Responses of root morphological and distribution variables of Signal grass (Urochloa decumbens) to cattle grazing in tropical pastures of Malaysia
Root variables | Treatment | SE | F | P | Soil depth (cm) | SE | F | P | Treatment × depth | ||||||||
moderate grazing | grazing exclosure | 0–10 | 10–20 | 20–30 | F | P | |||||||||||
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Length (cm) | 1064.36a | 1275.59b | 120.36 | 4.12 | 0.05 | 2104.69a | 948.91b | 406.33c | 90.54 | 290.76 | 0.0 | 2.85 | 0.06 | ||||
Diameter (mm) | 0.79a | 0.70a | 0.197 | 0.233 | 0.63 | 1.43 a | 0.42b | 0.39b | 0.083 | 12.34 | 0.002 | 0.23 | 0.64 | ||||
Surface area (cm2) | 264.14a | 210.97a | 36.40 | 2.11 | 0.16 | 580.37b | 81.41a | 50.90c | 28.97 | 132.00 | 0.0 | 0.43 | 0.53 | ||||
Volume (cm3) | 8.91a | 7.40a | 3.37 | 0.247 | 0.62 | 22.30b | 1.62a | 0.54c | 1.84 | 17.64 | 0.0 | 0.14 | 0.71 | ||||
Mass (mg) | 946.66a | 589.86b | 91.60 | 15.71 | 0.001 | 1595.33b | 573.06a | 136.40c | 82.61 | 103.67 | 00 | 5.64 | 0.07 | ||||
RLD (cm/cm3) | 2.12a | 2.55b | 0.24 | 4.12 | 0.05 | 4.28b | 2.19a | 0.80 c | 0.180 | 290.76 | 0.0 | 2.85 | 0.06 | ||||
SRL (cm/mg) | 1.36a | 3.68b | 0.371 | 39.16 | 0.00 | 1.95ba | 2.15a | 3.46b | 0.227 | 8.54 | 0.004 | 12.63 | 00 | ||||
RMD (mg/cm3) | 1.89a | 1.17b | 0.26 | 12.91 | 0.002 | 3.39 b | 1.14a | 0.38 c | 0.190 | 42.31 | 0.0 | 3.29 | 0.07 | ||||
SAD (cm2/cm3) | 0.53a | 0.42a | 0.07 | 2.11 | 0.162 | 1.15 b | 0.16a | 0.10 c | 0.058 | 131.99 | 0.0 | 0.43 | 0.53 | ||||
RVD (cm3/cm3) | 0.018a | 0.014a | 0.007 | 0.247 | 0.625 | 0.045b | 0.003a | 0.001c | 00 | 17.64 | 0.0 | 0.14 | 0.71 | ||||
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Means in a row with unlike letters differ at P < 0.05.
RLD: root length density, SRL: specific root length, RMD: root mass density, RSAD: surface area density, RVD: root volume density.
Table 3. Responses of root morphological and distribution variables of Carpet grass (Axonopus compressus) to cattle grazing in tropical pastures of Malaysia
Root variable | Treatment | SE | F | P | Soil depth (cm) | SE | F | P | Treatment × depth | ||||||||
heavy grazing | grazing exclosure | 0–10 | 10–20 | 20–30 | F | P | |||||||||||
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Length (cm) | 1010.1a | 1484.92b | 180.63 | 6.91 | 0.016 | 2837.30b | 665.33a | 239.89a | 200.06 | 93.10 | 0.0 | 1.16 | 0.30 | ||||
Diameter (mm) | 0.35a | 0.28b | 0.026 | 7.40 | 0.013 | 0.38b | 0.29a | 0.28a | 0.02 | 6.51 | 0.01 | 4.00 | 0.03 | ||||
Surface area (cm2) | 173.23a | 145.20a | 25.99 | 1.16 | 0.294 | 407.81b | 48.61a | 21.22a | 31.60 | 135.54 | 0.0 | 9.90 | 0.004 | ||||
Volume (cm3) | 2.47a | 1.34b | 0.368 | 9.53 | 0.006 | 5.12b | 0.35a | 0.25a | 0.48 | 79.17 | 0.0 | 16.79 | 0.001 | ||||
Mass (mg) | 663.83a | 481.23a | 124.20 | 2.16 | 0.157 | 1406.25b | 237.07a | 74.28c | 109.53 | 55.72 | 0.0 | 3.03 | 0.09 | ||||
RLD (cm/cm3) | 2.02a | 3.13b | 0.456 | 5.92 | 0.024 | 5.64b | 1.32a | 0.78c | 0.40 | 74.23 | 0.0 | 0.91 | 0.37 | ||||
SRL (cm/mg) | 3.00a | 5.41b | 0.71 | 11.46 | 0.003 | 2.53b | 4.09cb | 5.98c | 0.53 | 7.89 | 0.004 | 0.83 | 0.04 | ||||
RMD (mg/cm3) | 1.31a | 0.95a | 0.247 | 2.16 | 0.157 | 2.79b | 0.47a | 0.14c | 0.22 | 55.72 | 0.0 | 3.03 | 0.09 | ||||
SAD (cm2/cm3) | 0.35a | 0.31a | 0.058 | 0.51 | 0.482 | 0.81b | 0.10a | 0.07a | 0.06 | 122.90 | 0.0 | 10.43 | 0.004 | ||||
RVD (cm3/cm3) | 0.005a | 0.003b | 0.001 | 9.53 | 0.006 | 0.01b | 0.001a | 0.001a | 0.004 | 79.17 | 0.0 | 16.79 | 0.001 | ||||
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Means in a row with unlike letters differ at P < 0.05.
RLD: root length density, SRL: specific root length, RMD: root mass density, RSAD: surface area density, RVD: root volume density.
Root length and RLD of both grass species were affected (P < 0.05) by grazing and soil depth, but were unaffected (P > 0.05) by the interaction between soil depth and grazing (Tables 2 and 3). Mean root length of grazed Signal grass and Carpet grass was 18 and 38% smaller (P < 0.05) than that in their ungrazed pasture, respectively. Root diameter of heavily grazed Carpet grass was affected (P < 0.05) by grazing treatment, soil depth and their interaction. Mean root diameter of grazed Signal grass and Carpet grass was 12% and 22% greater (P < 0.05) than that in the ungrazed pasture, respectively (Table 3).
Root surface area and SAD of Signal grass were affected (P < 0.05) only by soil depth and not by grazing or their interactions in LMG strategy. Root volume and RVD of Signal grass were only affected (P < 0.05) by soil depth, but not by moderate grazing or their interactions in LMG pasture (Tables 2). In STG pasture, root surface area and SAD of Carpet grass was not affected (P > 0.05) by grazing, but affected by soil depth and its interaction with grazing (P < 0.05). These variables were affected (P < 0.05) by heavy grazing, soil depth and their interactions in SHG pasture. Mean root volume was 59% greater (P < 0.05) in heavily grazed Carpet grass compared to its grazing exclosure (Tables 3).
Root mass and RMD of Signal grass were positively affected (P < 0.05) by moderate grazing and soil depth, but not by their interactions. Mean root mass in grazed pasture was nearly 46.5 % greater than that in ugrazed pasture of Signal grass in the LMG pasture (Tables 2). Root mass and RMD of Carpet grass were only affected (P < 0.05) by soil depth, but not by heavy grazing and the interaction between them in SHG pasture (Tables 3). Specific root length (SRL) of both grass species was affected (P < 0.05) by grazing, soil depth and their interactions. Grazed pasture plants had nearly 92 and 57% less SRL in LMG and SHG pastures, respectively (Tables 2 and 3).
Root mean length, diameter, surface area, volume and accordingly length, surface area and volume densities did not vary between grazed and ungrazed in Signal grass. However, root length, diameter, volume and accordingly length, surface area and volume densities were the traits that varied between grazed and ungrazed at heavily grazed pasture of Carpet grass. Overall, moderate grazing had no significant negative impact on the root traits of Signal grass over time. Conversely, heavy grazing affected roots significantly at Carpet grass.
3.3. Relationships between root traits and soil depths
The relationships between root length and volume densities (RLD and RVD) with soil depths based on individual root cores of A. compressus were best depicted by exponential followed by power functions. The coefficients of determination (R2) for root length and root volume densities were 0.58 and 0.64 for exponential function and 0.58 and 0.69 for power function, respectively. Root surface area density and soil depths relationship was best described by power (R2 = 0.81) and logarithmic (R2 = 0.80) functions. Highest coefficient of determination for the relationship between root mass density and soil depth was signalized by power function (R2 = 0.70). The linear function was the poor predictor of the relationship between measured root distribution characteristics of A. compressus with soil depth among the functions (Table 4).
The exponential and logarithmic functions with similar coefficients of determination (R2 = 0.72) were the best function in description of root length density (RLD) and soil depth for Urochloa decumbens. The relationships between root surface area and volume densities (RSAD and RVD) with soil depths were best explained by power and exponential functions. Similar coefficients of determination (R2) of 0.82 and 0.81 were explored for both surface and volume densities, respectively. Root mass density (RMD) and soil depth relationship was best depicted by exponential (R2 = 0.81) function (Table 5). Oliveira et al., (2000) cited that the relationship between RMD of Italian ryegrass (Lolium multiflorum) and soil depth was closely described by an exponential equation. The linear function was poor predictor of the relationship between measured root distribution characteristics of improved pasture and soil depths among the functions. Greenwood and Hutchinson, (1998) found that power and reciprocal functions were the strongest and linear function was the poorest predictor in description of root distribution and soil depth relationships at Phalaris (Phalaris aquatica) and White clover (Trifolium repense) pastures of NSW, Australia. Mousel et al., (2009) reported inverse relationships of Big bluestem (Andropogon gerardii) root characteristics including root mass, surface area and volume densities with soil depth increment. An exponential relationship between root length density and soil depth fits root data of both A. compressus and U. decumbens in this study. Our finding is supported by several authors, for example, Greenwood et al., (1982), Greenwood and Hutchinson, (1998) and Oliveira et al., (2000) who reported exponential function with coefficients of determination of 0.90, 0.74 and 0.98 for relationship between grass root length density and soil depth, respectively.
In this study, coefficients of determination for exponential function were 0.58 and 0.72 for A. compressus (tropical native grass) and U. decumbens (tropical improved grass) with regard to root length density, respectively. Relatively low coefficients (R2) in this study can be attributed to sampling depth, as in previously mentioned studies the sampling depth was much deeper than this study. The difference between coefficients between the two study areas can be related to different rooting system of grass species that rooting system of native and improved grasses are not similar. Overall, power and exponential functions depicted well the relationship between root distribution characteristics and soil depth for both species in this study.
There were significant differences (P < 0.05) among consecutive depth increments in top 30 cm in all root traits at both studied species. All measured root traits showed an inverse relationship by soil depth increment. Root variables of both grass species showed higher proportion in 0-10 cm soil depth (Table 6). This indicates that root system of both tropical grasses are largely distributed in surface soil layer. The higher proportion of grass plants root in upper (0-10 cm) soil layer supported by many researchers (for example, Mathew et al., 1991; Greenwood and Hutchinson, 1998; Lodge and Murphy, 2006).
Table 4. Relationships between root characteristics as dependent variables (Y) and soil depth (cm) as independent variables (X) for individual root samples of Axonopus compressus
Function | Equation | Root characteristics | a | b | Coefficient of determination (R2)* |
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Linear | Y = a - bX | RLD (cm/cm3) | 5.27 | -1.753 | 0.43 |
RSAD (cm2/cm3) | 1.22 | -0.448 | 0.70 | ||
RVD (cm3/cm3) | 0.013 | -0.005 | 0.47 | ||
RMD (mg/cm3) | 3.343 | -1.206 | 0.58 | ||
Exponential | Y = ae-bX | RLD (cm/cm3) | 9.00 | -1.102 | 0.58 |
RSAD (cm2/cm3) | 3.688 | -1.715 | 0.75 | ||
RVD (cm3/cm3) | 0.034 | -1.771 | 0.64 | ||
RMD (mg/cm3) | 9.340 | -1.629 | 0.67 | ||
Power | Y = aX- b | RLD (cm/cm3) | 3.25 | -1.965 | 0.58 |
RSAD (cm2/cm3) | 0.790 | -3.153 | 0.81 | ||
RVD (cm3/cm3) | 0.007 | -3.250 | 0.69 | ||
RMD (mg/cm3) | 2.107 | -2.932 | 0.70 | ||
Logarithmic | Y = a - b log X | RLD (cm/cm3) | 3.72 | -3.261 | 0.48 |
RSAD (cm2/cm3) | 0.832 | -0.847 | 0.80 | ||
RVD (cm3/cm3) | 0.009 | -0.009 | 0.55 | ||
RMD (mg/cm3) | 2.292 | -2.264 | 0.66 | ||
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* All coefficients (R2) are significant at the 0.01 level
Table 5. Relationships between root characteristics as dependent variables (Y) and soil depth (cm) as independent variables (X) for individual root samples of Urochloa decumbens
Function | Equation | Root characteristics | a | b | Coefficient of determination (R2)* |
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Linear | Y = a - bX | RLD (cm/cm3) | 5.54 | -.162 | 0.71 |
RSAD (cm2/cm3) | 1.622 | -0.555 | 0.68 | ||
RVD (cm3/cm3) | 0.003 | -0.001 | 0.68 | ||
RMD (mg/cm3) | 4.629 | -1.544 | 0.65 | ||
Exponential | Y = ae-bX | RLD (cm/cm3) | 9.394 | -0.850 | 0.72 |
RSAD (cm2/cm3) | 3.856 | -1.313 | 0.81 | ||
RVD (cm3/cm3) | 0.008 | -1.313 | 0.81 | ||
RMD (mg/cm3) | 12.947 | -1.384 | 0.75 | ||
Power | Y = aX-b | RLD (cm/cm3) | 4.190 | -1.484 | 0.69 |
RSAD (cm2/cm3) | 1.143 | -2.350 | 0.82 | ||
RVD (cm3/cm3) | 0.002 | -2.350 | 0.82 | ||
RMD (mg/cm3) | 3.447 | -2.402 | 0.71 | ||
Logarithmic | Y = a - b log X | RLD (cm/cm3) | 4.043 | -2.928 | 0.72 |
RSAD (cm2/cm3) | 1.132 | -1.036 | 0.75 | ||
RVD (cm3/cm3) | 0.002 | -0.002 | 0.75 | ||
RMD (mg/cm3) | 3.229 | -2.816 | 0.68 | ||
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* All coefficients (R2) are significant at the 0.01 level.
Table 6. Distribution and spatial variability of root traits (Y) and soil depth (X) of the studied grass species
Species | Depth (cm) | RLD | SE | % of total | RMD | SE | % of total | RSAD | SE | % of total | RVD | SE | % of total |
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Axonopus compressus | 0-10 | 5.64 | 0.439 | 72.86 | 2.79 | 0.331 | 81.81 | 0.182 | 0.065 | 52.29 | 0.01 | 0.001 | 83.33 |
10-20 | 1.32 | 0.247 | 17.05 | 0.472 | 0.102 | 13.84 | 0.097 | 0.020 | 27.87 | 0.001 | 00 | 8.33 | |
20-30 | 0.78 | 0.306 | 10.07 | 0.148 | 0.032 | 4.34 | 0.069 | 0.027 | 19.82 | 0.001 | 00 | 8.33 | |
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Equation | RLD = 3.25 (X) 1.965 R2 = 0.58 | RMD = 2.107 (X) 2.932 R2 = 0.70 | RSAD = 0.790 (X) 3.153 R2 = 0.81 | RVD = 0.007 (X) 3.250 R2 = 0.69 | |||||||||
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Urochloa decumbens | 0-10 | 4.18 | 0.150 | 60.84 | 3.39 | 0.369 | 69.04 | 1.16 | 0.092 | 81.69 | 0.044 | 0.010 | 91.66 |
10-20 | 1.88 | 0.178 | 27.36 | 1.14 | 0.149 | 23.21 | 0.16 | 0.026 | 11.26 | 0.003 | 0.001 | 6.25 | |
20-30 | 0.81 | 0.097 | 11.79 | 0.38 | 0.093 | 7.73 | 0.10 | 0.013 | 7.04 | 0.001 | 00 | 2.08 | |
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Equation | RLD = 9.394e0.850 (X) R2 = 0.72 | RMD = 12.947e1.384 (X) R2 = 0.75 | RSAD = 1.143 (X) 2.350 R2 = 0.82 | RVD = 0.002 (X) 2.350 R2 = 0.82 | |||||||||
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4. Discussion
4.1. Shoot growth
We found no evidence that moderate and heavy rotational grazing impaired the health of Signal grass (Urochloa decumbens) and Carpet grass (Axonopus compressus), respectively, grown in the humid tropics of Malaysia. On the contrary, grazing enhances forage production of Signal grass and the regrowth potential of both species by producing greater tillering and root mass. This response appears to be related to defoliation by grazing that promotes overcompensation through increase in tillering and regrowth rate and the reduction of litter by trampling or grazing that releases shading.
The increase in herbage production in grazed improved pasture of Signal grass may be associated with improved plant nutrients uptake in such pastures as soil readily available nutrients increase in pastures with grazing (Risser and Parton, 1982; Wang et al., 2023). Consistent with our findings of no significant negative impact of STG on herbage production in Carpet grass, Li et al., (2009) found higher herbage production in pastures with heavy and moderate grazing intensities of rough fescue (Festuca campestris) grassland in Canada. No negative impact of STG on herbage production can be explained by compensation for tissue removal by plants (Langlands and Bennett, 1973) which increase in herbage mass occurs when overcompensation happens (Li et al., 2009). Regrowth is defined as the increase in size, volume and mass of a plant as a function of time (Pinto et al., 2004). Increase in regrowth rate of Signal grass under long-term moderate grazing can be primarily ascribed to a higher rate of biomass recovery and stimulation of plant by animal biting to compensate removed tissues (Sulistijo et al., 2021). Moreover, high regrowth potential of grass under grazing may be attributable to adaptation of such grasses to grazing over time. Stur and Shelton (1990) stated that Axonopus compressus, dominant grass species in native pastures of Ladang site, is renowned for its ability to endure heavy grazing intensity.
Tiller density is the most important parameters of pasture structure and dynamics (Sbrissia et al., 2004). Pastures under cattle grazing had greater reproductive and vegetative tiller densities in this study (Table). The larger number of tillers accelerates re-foliation and herbage production accordingly (Hoglind et al., 2005). Greater tiller density in grazed pastures is likely related to higher soil nutrients level, moderate amount of accumulated litter, higher rate of compensation of tissue removal in such pastures. Tillers were denser and shorter in grazed pastures particularly in heavily grazed native pasture of Carpet grass (Table 1). High density and small size of tillers can be directly attributable to above-ground morphological adaptation to herbivory grazing pressure (Dawson et al., 2000). Moreover, both grasses are rhizomatous and that grazing enhanced tillering. Individual tillers are usually associated with roots at their node with the rhizome/stolon, and therefore explaining the greater mass and, perhaps the shorter root length.
Our result on litter biomass is in agreement with findings of Donkor et al., (2001) and Xie and Wittig (2004) that litter biomass production decreased in pastures with grazing. Greater litter production in grazing exclosure can be ascribed to soil nutrients level. As in pastures with livestock grazing, available form of nutrients for plant is greater than pastures without livestock. Thus, there is sufficient supply of nutrient for plant uptake in grazed pastures (Deutsch et al., 2010). This causes a delay in leaf and shoots senescence which may happen faster in insufficient soil nutrients and competitive environments. High senescence rate increase litter production (Li et al., 2009).
4.2 Root characteristics
Early studies of plant root under pasture were usually limited to root mass data (Greenwood and Hutchinson, 1998). Measurement of root mass does not facilitate interpretation of root function and may bias interpretation of treatment (Van Noorwijk, 1993). Image analysis techniques have now become available that enable to estimate root length, diameter, surface area and etc. Accurate estimation of these parameters can provide valuable data for understanding root function. In this study root morphological traits including root length, diameter, surface area, and volume were estimated by using modern techniques to compute root distribution characteristics and to quantify root response to grazing management strategies.
Root diameter, volume and surface area of A. compressus were smaller compared with U. decumbens. Differences in measured root parameters of both species may be related to the different grass species in these areas. Grass plants of the native pasture mainly consist of native perennials with finer roots. Different species utilize various strategies with respect to root traits to cope with grazing may be important mechanisms that allow grassland plants to persist in spatially and temporally heterogeneous environments (Ajorlo et al., 2014). The results of this study thus implicate plasticity of structural traits as a major determinant of the species-specific responses of environmental variation. The response of root morphological traits to grazing may also be contingent on other environmental conditions, i.e., grazing severity, frequency, timing, soil moisture, soil compaction, and soil type. Consequently, responses to grazing may differ among species and needs to be investigated more.
We observed no evidence that moderate or heavy rotational grazing in a humid tropical grassland community of Signal grass and Carpet grass impaired root development that was detrimental to their health. On the contrary, root mass, surface area and most concomitant variables associated with them, were either greater with grazing or unaffected by it. This response would seem reasonable as the roots and aboveground portion of the plant are interdependent and further supports the conclusion that rotational grazing benefits these grasslands. However, of the root variables measured, only length was reduced by grazing in both grasses. Observation from other well documented cases where judicious disturbance either from grazing or fire was essential in maintaining grasslands supports this finding (Oliveria et al., 2004; Mousel et al., 2005; Shakhane et al., 2013).
Longer roots are important as available nutrients become more limiting and competition for them becomes more severe (Chen et al., 2006). In contrast, grazed pastures contain higher level of nutrients due to a more rapid turnover of nutrients through cattle excreta and trampling (Peng et al., 2022). Consequently, root elongation and proliferation in pastures with animal grazing is lower due to the availability of sufficient nutrients in soil (McInenly et al., 2009; Ajorlo, 2010). While grazing reduced root length for both Signal grass and Carpet grass, their root length densities were well within the range proposed by van Noordwijk (1993) for uptake of needed water and phosphorus.
Root surface area is an important factor for absorption of relatively immobile nutrients and has significant role across soil-root interface (Greenwood and Hutchinson 1998; Peng et al., 2022). The number of grazing events and the length of recovery intervals between the grazing were reported as principal factors influencing root surface area (Mousel et al., 2005). Similar to our study, Greenwood and Hutchinson (1998) report that surface area density was generally similar between grazed and ungrazed treatments in temperate pastures grazed at low and high stocking rates for 30 years in New South Wales. Greater length and diameter of roots over soil depth resulted in markedly higher root surface area densities. Correlation coefficient (r) of root surface area density with length and diameter were 0.80 and 0.79 in our study.
Root volume of Signal grass and Carpet grass was highly correlated with root diameter rather than root length. Correlation coefficients of Signal grass root volume with length and diameter were 51 and 95%, respectively, and 74 and 77% for Carpet grass. Root volume is a function of root length and diameter. Engel et al., (1998) indicated that root length probably is the principal factor affecting root volume of grasses. Conversely, Mousel et al., (2005) observed that root diameter rather than root length was the key variable influencing root volume of big bluestem (Andropogon gerardii).
Our observation that grazed grasses had greater total root mass than ungrazed grasses is supported by Milchunas and Lauenroth (1993). In contrast, Dawson et al., (2000) and Oliveria et al., (2004) reported that root mass in grazed pastures was lower than in the ungrazed pastures. High root mass grazed pastures can be attributable to the absence of cultivation practices in the in pastures and the presence of unknown proportion of dead and non-functional roots in samples. Since cattle grazing accelerate root death by treading and defoliation, high amounts of dead material can be expected in root samples from grazed pastures (Ajorlo et al., 2014). Additionally, high proportion of fine roots was visually observed in root samples from grazed pastures compared with ungrazed pasture during the root washing process. Fine roots can make very large contribution to total root mass (Greenwood and Hutchinson, 1998). Dawson et al., (2000) stated that as it is difficult to extract and discriminate live and active roots from inactive and dead roots and since root production and root mortality occur simultaneously; then root mass cannot be a strong reflection of below-ground growth.
Specific root length (cm/mg) is the root length produced by a unit of root mass. In this study, grazed pastures had nearly 47 and 45% less specific root length in LTG and STG pastures, respectively (Tables 2 and 3). Arredondo and Johnson (2009) found that grazed plant with 80% removal of standing biomass produced half the SRL compared to ungrazed plants. Conversely, Anderson et al., (2007) indicated that clipping had no clear effect on the SRL in Andropogon greenwayi, Sporobolus kentrophyllus and Festuca idahoensis. The higher SRL we found in our study where grazing was excluded may be attributed to root foraging viz. the extension of root system in search of soil nutrients due to limited resources and highly competitive condition. SRL links to several morphological and physiological root variables such as increased root axis extension, proliferation (lateral growth), relative growth rate and resource uptake per unit mass. SRL showed negative correlations with root length, diameter and mass. Correlation coefficients (r) of SRL with root length, diameter and mass were –23, –34 and –57, respectively. These coefficients indicate that root mass followed by diameter have more effects on SRL value. Wherever root mass and/or diameter is higher, greater SRL would be expected. Consequently, high value of SRL in ungrazed pastures can be explained by those negative correlations. Greater SRL value improves the ability of grasses to uptake more nutrient and water in competitive environments (Arredondo and Johnson, 2009). Specific root length was also affected significantly by soil depth (Tables 2 and 3). SRL increased with increasing soil depth. The deepest measured depth (20–30 cm) had the highest value of SRL due to low root length, diameter and mass in this depth.
Since pastures of both study areas remained strongly dominated by perennial grasses, i.e., no appreciable encroachment of invasive species; differences in root morphology and distribution as a result of cattle grazing in this study are attributable to responses by the perennial grass plants of itself. It should be emphasized that the results of root data interpretation in this study only indicate the presence of roots, not their functionality. The impact of grazing treatments on root morphology and distribution can be masked by the presence of old, non-functional roots or differing requirements for functionality to uptake ions. Consequently, root data should be interpreted with some cautions (Lodge and Murphy, 2006)
5. Conclusions
Defoliation of vegetation via grazing can be a major destructive process in pasture ecosystems. Knowledge on the response of both above- and below-ground processes of tropical pastures to grazing strategies is important to adjusting stocking rate. This study aimed to quantify the responses of Signal grass (Urochloa decumbens) and Carpet grass (Axonopus compressus) shoot and root systems to long-term moderate and short-term heavy, respectively, rotational grazing by cattle in tropical pastures. Our results indicate that shoot growth of studied grass plants tend to increase in pastures under both long-term moderate and short-term heavy grazing. Signal grass root was not negatively affected by moderate grazing. Short-term heavy grazing had greater impact on root characteristics than long-term moderate grazing. Besides grazing strategy, the response of shoot and root variables to grazing may also be contingent on other environmental variables, i.e., soil compaction, and soil texture and type. Consequently, the response of Signal grass and Carpet grass shoot and root systems to grazing may differ in other environments and needs to be investigated more. Overall, power and exponential functions depicted well the relationship between root distribution characteristics and soil depth for both species in this study. It should be emphasized that our findings in this study only indicate the presence of root variables, not their functionality. The impact of grazing on root morphology and distribution can be masked by the presence of old, non-functional roots or differing requirements for functionality to uptake ions.
Conflict of interest statement:
The authors declare that they have no conflict of interest.
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