Changes in Species Diversity and Functional Diversity of Vegetation under Different Grazing Intensities in Changizchal Rangelands, Mazandaran Province, Iran
Mansoureh Kargar
1
(
PhD Graduated of Rangeland Science, Watershed and Natural Resources Administration of Alborz Province, Karaj, Iran
)
Majid Sadeghinia
2
(
Assistant Professor, Department of Nature Engineering، Factually of Agriculture and Natural Resources, Ardakan University, Iran
)
Sara Farazmand
3
(
Assistant Professor, Department of Rangeland and Watershed Management, Faculty of Natural Resources, Behbahan Khatam Alanbia University of Technology, Iran
)
Keywords:
Abstract :
Changes in Species Diversity and Functional Diversity of Vegetation under Different Grazing Intensities in Changizchal Rangelands, Mazandaran province, Iran
Abstract
Different indices of functional diversity as: functional richness (FRic), functional evenness (FEve) and functional divergence (FDiv), give help to clearer and more broadly applicable understanding of the relationship between plant diversity and ecosystem functioning. Therefore, this study was carried out to evaluate changes in species diversity and functional diversity of vegetation under different grazing intensities in relation to soil physic-chemical properties in changizchal rangelands, Mazandaran province, Iran. During the spring and summer of 2014, three functional traits including Specific Leaf Area (SLA), Vegetation Height (VH), and Leaf Dry Matter Content (LDMC) were measured in three grazing intensities (low, moderate and high). Taxonomic diversity was quantified using several indices including Species richness (S), Shannon (H), Evenness (E) and Simpson (D). In addition, functional diversity was quantified using single trait-based (FDvar) and multi trait-based indices (functional richness (FRic), functional divergence (FDiv), and functional evenness (FEve)). The result showed that functional richness increased with species richness at moderate grazing. The FDvar of VH significantly increased in light grazing, while the FDvar of SLA showed a moderate grazing. The low grazing induced increase in the FDive and FEve coupled with decreasing soil organic carbon (P<0.05). The FDvar for SLA had positive relationship with higher soil N and P in low grazing. Grazing in changizchal rangelands tends to increase competition for soil N and P, resulting in an increase in the functional richness in grazed plant communities. The present study highlights the potential importance of low to moderate grazing intensities in mediating and reducing competition between plants for nutrient resources.
Key words: Biodiversity, Rangeland stability, Grazing management; Leaf functional traits, Rangeland ecosystem
Introduction
Rangeland ecosystems are among the main territorial ecosystems which support several functioning and services for human society (Omidipour et al., 2021). The impact of biotic stress, particularly grazing pressure, on plant diversity is quite controversial. On one hand, grazing is considered as a key factor to promote diversity, on the other hand, grazing can reduce plant diversity and lead to the homogenization of rangeland (Teague and Barnes, 2017). But most of grazeable rangelands of the world are under a continuous or relatively unmanaged grazing intensity which is in excess of carrying capacity. This mismanagement has resulted in degraded vegetation and soils, as well as loss of soil productivity and biodiversity (Tahmasebi et al., 2017).
In Iran, overgrazing by livestock is a major driver of rangeland degradation, mainly through the reduction of productivity and resilience (Jafarian et al., 2018). Overgrazing is among the main causes of vegetation degradation because it diminishes vegetation cover and disrupts important ecological processes such as grass recruitment and nutrient cycling (Chillo et al., 2017). In Iran, rangelands occupy about 90 million ha, accounted for 54.6% of the total area of the country and 65% of the natural resources, with more than 8,000 species exposed to this disturbance (Jafarian et al., 2019). In particular, the 378,000 ha of Caspian rangelands in Mazandaran province, Iran are characterized by high plant diversity and a good condition because of climate conditions (Jafarian et al., 2019). But due to mismanagement and high sheep and cattle density, biodiversity has been seriously reduced (Jafarian et al., 2019). Plant functional characteristics play an important role in predicting patterns of species composition, community structure and their response to livestock grazing, landuse changes, vegetation succession, and abandoned fields that have led to significant ecological uptake (Ricotta and Moretti, 2011; Spasojevic and Siding, 2012; Karadimou et al., 2014; Chillo et al., 2017; Rahmanian et al., 2019; Jäschke et al., 2020). In order to understand the response of plant communities to livestock grazing and its effect on ecosystem functioning, it is necessary to focus on more than just individual species and their identity (Dubuis, 2013; Jafarian et al., 2018). The plants in a community should be partitioned into different groups based on their functional traits. Plant functional characteristics play an important role in predicting patterns of species composition, community structure and their response to environmental changes that have led to significant ecological uptake (Casanoves et al., 2011). For example, an increase in the diversity of a trait such as Specific Leaf Area (SLA) is associated with increased niche differentiation in response to the competition for limiting resources such as light and nutrients (Kraft et al., 2008; Dwyer et al., 2014). The analysis of functional diversity can clarify the effects of increasing livestock grazing on ecosystem functioning. Many studies have been carried out on the comparison of indigenous varieties and species richness within the country. Previous studies in Iran have indicated that intraspecific variation of individual traits can also play an important role in plant response to changes in environmental factors (Heidari and Saeedi Garghani, 2013; Mansoori et al., 2013; Jafarian et al., 2018). In this regard, we hypothesized that: i) Functional richness in areas with moderate grazing is higher than those with low intensity of grazing. ii) The response of plant communities to graze in mountain rangeland may depend on the water availability and soil fertility. In this paper, we assessed the functional basis of changes in the plant species and functional diversity of mountain rangeland, in the north of Iran under different grazing intensities. This research aimed to determine the effects of grazing intensity on functional diversity through single trait and multiple- traits indices, and the effect of such changes on soil properties.
Materials and Methods
Study site
The study area, Changizchal rangelands, is located in the North part of Iran (52°11′–52°49′ N; 35°15′-35°49′E). It covers ca. 2415.52 ha, with the elevation ranging from 2500 to 3100 m (Fig.1). It has a semi-arid cold climate with the mean annual temperature of 12.79°C; and the mean annual precipitation of 652 mm. The soil type is sandy-loamy and silts. The experiment was carried out in low, moderate and heavy grazing sites, which were adjacent to each other in our study area. Grazed rangelands at all sites are dominated by Heracleum persicum Desf (Apiaceae), Astragalus aegobromus Boiss. & Hohen (Fabaceae) and species Phlomis cancellata Boiss. & Hohen (Lamiacea), Achillea millefolium L and Erigeron uniflorus L and Tragopogon graminifolius DC (Asteraceae), Bromus tomentellus Boiss and Poa pratensis (Poaceae) (Jafarian et al., 2019).
Fig. 1. The Changizchal rangelands located in Mazandaran province, Northern Iran
Sampling design
Three different grazing sites including low, moderate, and heavy grazing intensities were established in the area. Vegetation was grazed by sheep. From mid spring and summer of 2014, sampling was done in a 1×1 m plots within each grazing intensities. In each grazing intensities, in total 150 sampling plots were selected randomly. The plots were separated by 100 m at each site.
Functional traits measurements
The leaves were weighed, scanned and analyzed in the laboratory using the Leaf area matter software to measure their surface. We also measured the leaf dry mass after drying and weighing the leaves. The vegetation height was measured in the field as the distance between the top of the photosynthetic tissue and the ground (Dubuis, 2013). Specific leaf area (SLA) was calculated as the ratio of the leaf surface to its dry mass, expressed in mm2 mg-1 (Dubuis, 2013). Leaf dry matter content (LDMC) is the ratio of the leaf dry mass to its saturated fresh mass (in mg g-1) (Rossier, 2011).
Soil measurements
The soil data were recorded within 50 plots at 0-30cm depth throughout the study area. The soil samples were air-dried and passed through a 2 mm sieve to prepare them for experiments. The used methods were as follows: the Bouyoucos hydrometer method for soil texture, the Kjeldahl method for total nitrogen and the modified Walkley- Black wet oxidation procedure for organic carbon content (Baize, 2000). Potassium was determined after extraction with 1N ammonium acetate adjusted with pH 7, total phosphorus was determined calorimetrically from wet digestion with H2SO4 + HClO4, CaCO3 was measured following the procedure outlined in moisture saturation was the difference between weight of saturated and oven-dried (105°C during 24 h) soil. Soil pH was determined in a soil/water solution with a volume ratio of 1:1 (Pellissier et al., 2010).
Functional and species diversity indices
To measure species diversity in each quadrat, we calculated species richness, Shannon entropy of true species diversity, and the Simpson index of species evenness based on species number and relative abundance (Jost 2006). As a single trait index, we calculated functional divergence (FDvar) considering individually SLA, LDMC, and VH for each grazing area, using the FD package in R (Laliberte and Shipley, 2010). The functional divergence index is essentially the variance in the values of the characteristics of the species present in a site, and the squared residuals due to the abundance of used species (Mason et al., 2012). It is defined as:
Where: 5 is a scaling factor used to define the index over a range of 0–1; V is the weighted variance of trait X, expressed as:
This index takes one of the traits at a time and uses the relative abundance of any species (wi) to load its contribution to diversity in a community.
The mean of lnxi is weighted by the abundance as:
Where:
Multi-traits diversity indices including functional Richness (FRic), Functional Evenness (FEve) and Functional Divergence (FDiv) were used to evaluate the functional diversity for leaf traits (Villeger et al., 2008; Mouchet et al., 2010). These indices are based on the frequency of species in each plot and Gower distances matrices from five traits in grazed plots (Laliberte and Shipley, 2010).
Data Analysis
To investigate the effect of grazing on species diversity, single-trait and multi-trait functional diversity in three study sites, we used a linear-mixed model with residual maximum likelihood (REML): respons ~ Site/Grazing. Here, the diversity indices were included as response variables along with ‘Grazing’ as nested fixed factors within each site; individual quadrats were taken as a random factor to account for any spatial autocorrelation. The Ime4 package in R was used to perform mixed models (Bates et al., 2011). We used generalized canonical discriminant analyses (gCCA) with a nested linear model to examine and visualize linkages among the FD of individual traits and soil nutrient availability in grazed plots across the three study sites. The gCCA was performed using the Candisc package (Friendly and Fox, 2013).
Results and Discussion
The effects of grazing on the functional diversity of single-traits (FDvar)
The FDvar for leaf matter dry content (LDMC) significantly decreased in heavy grazing but increased at moderate grazing (Table 1). The FDvar of vegetation height (VH) significantly increased in moderate grazing and FDvar of SLA significantly increased in heavy grazing. The relationships between FDvar for SLA, VH and LDMC and soil properties in three grazing system were assesd using scatter plot two main canonical functions CAN1 and CAN2. The FDvar for SLA and VH had positive relationship with soil N and P content. The increase in FDvar from LDMC was associated with the reduction of organic carbon and increase in soil total nitrogen (Fig. 2). FDvar of VH significantly increased in moderate grazing site but decreased at low grazing site. The mean value of single-traits (FDvar) such as leaf dry matter content, SLA and vegetative height at each treatment tended to decrease at moderate and high grazing. LDMC is more influenced by soil factors than SLA and VH because it is related to the storage of plant resources, which is itself linked to the quality of nutrients present in the soil and indirectly linked with the pH that influence nutrient availability (Fig. 2). These results, with recent observations, suggest that the response of functional diversity to environmental change does not only relate to species diversity (Sımova et al., 2014) as the response of the community to grazing pressure may be complex (Karadimou et al., 2014). A community with high SLA and consequently low LDMC may have reduced amount of litter. Also, plants with lower LDMC may have higher plant component digestibility, but lower leaf proportion (Cornelissen et al., 2003). Low SLA and VH, and high LDMC are traits related to a species that may grow slowly and grow on soils with poor nutrients and acid soils (Dubuis, 2013).
Table 1. Results of linear-mixed modelling for effect of grazing on functional diversity (FDvar) of single traits, functional diversity of multi-trait and species diversity.
Diversity indices | AIC/BIC | Heavy grazing | Moderate grazing | Low grazing |
Functional diversity of single traits |
|
|
|
|
Leaf Matter Dry Content | 193/125 | -0.04± 0.01* | 0.12±0.01* | 0.34±0.05 |
Species Leaf Area | -214/-167 | -0.17±0.008* | 0.15±0.01 | 0.21±0.03* |
Vegetation Height | -182/-173 | 0.11±0.02 | 0.16±0.005 | -0.12±0.08* |
Functional diversity for multi-trait |
|
|
|
|
Functional Richness (FRic) | 235/259 | 3.21±1.1 | 4.11±1.01* | 2.98±0.09* |
Functional Divergence (FDiv) | -178/-192 | 0.003±0.008 | -0.004±0.06 | 0.01±0.04 |
Functional Evenness (FEve) | 76.4/-32.1 | -0.02±0.077 | -0.001±0.004 | 0.08±0.02 |
Species diversity |
|
|
|
|
Species richness | 374/421 | -1.4±0.87 | 1.12±1.14* | 0.92±1.11* |
Shannon diversity | 48.6/32.7 | 1.1±1.23* | 1.9±1.2 | 1.77±0.23 |
Simpson evenness | 422/369 | 32.1±22.76 | 7.43±1.88 | -7.90±3.67 |
Simpson diversity | -279/-261 | -1.67±0.05 | -3.45±1.77* | -3.15±2.19 |
AIC : Akaike information criterion, BIC: the Schwarz’s Bayesian Information Criteria. Value = slope value + standard error with bold entries indicating (p<0.05), * indicating (p<0.01). The valus with positive and negative signs indicate increased and decreased diversity indices.
Fig. 2. Generalized canonical discriminant analysis showing links among functional diversity (FDVar) of individual leaf traits, specific leaf area (SLA), leaf dry matter content (LDMC), vegetation height (VH) and soil N, P, K.
The effect of grazing on the functional diversity for multi- traits and species diversity
Functional richness (FRic) significantly increased in moderate and low grazing. Functional divergence (FDiv) significantly increased in moderate grazing (Table 1). The low grazing induced increase in the FDiv and FEve coupled with decreasing soil organic carbon (P<0.05)(Fig.3).
Functional evenness did not change in the moderate grazed site, and it increased in low grazed site (Table 1; Fig. 3). Functional richness (FRic) in moderate grazing had significantly change be due to an intermediate disturbance type of response, as found in other rangelands for species diversity. The results showed that functional richness significantly increased in moderate grazing and low grazing. The low grazing increases plant productivity by increasing the amount of plant litter in functional groups, which may increase the C and N dynamics by increasing root production. This may be due to the fact that in the study area, with increasing intensity of grazing, shrubs increase and as a result, the richness of functional richness. The higher the functional richness, the more different the species is in terms of function, i.e., the range of nutrient source occupied by the ecological nests of the species. Functional divergence index (FDiv) indicates the nesting differences of species on the vector of nutrient resources. High divergence in function indicates that the species has large nesting differences over food resources, resulting in less competition (Cingolani et al., 2005). The results showed that the highest amount of FDiv is related to low grazing intensity. This research confirms that the variability of this trait was low and it has less tolerance against physical hazards such as animal grazing and wind. This idea has been used for the differences in the performance of ecological systems (Jafarian et al., 2018). Communities with high divergence increase the performance of the ecosystem as a result of the proper use of nutrient sources, which is consistent with the findings of other researchers (i.e., De Bello et al., 2012; Zhang and Lefing, 2015).
The effect of grazing on the species diversity
The Species richness significantly increased in low and moderate grazing but Shannon diversity increased at heavy grazing. The results showed that Simpson diversity significantly decrease in moderate grazing (Table 1). Shannon diversity in high grazing rates is due to the inability of plants to grow again after disturbance and the emergence of dominant non-palatable species (Cingolani et al., 2005; Petchey and Gatson, 2006). In addition, a significant change in the between different functional groups may be due to the complementary role; species regeneration, and species pool size (Niu et al., 2015).
The low grazing induced increase in the Species richness, Shannon diversity and Simpson evenness coupled with increased soil organic carbon (P<0.05)(Fig.3). Some studies have shown that increasing light availability and low grazing can lead to excessive complications of bed in herbaceous ecosystems (Mansoori et al., 2013).
Figure. 3. Generalized canonical discriminant analysis showing the influence of species and functional diversity in the suite of multi- traits at each of the three study sites (FRic: Functional Richness; FDiv: Functional Divergence; FEve: Functional Evenness; S: Species richness; H: Shannon species diversity; E: Simpson species evenness; D: Simpson species diversity).
Conclusion
The results of this study indicates that functional diversity is higher in moderate and low grazing intensities probably due to the competition of plants with each other and the existence of good reproduction in these two sites. It is expected that moderate grazing promotes diversity of plant communities by reducing opportunities for an exclusion of competition among the subdominant species (Olff and Ritchie, 1998). We observed that the species diversity and evenness diversity were increased under increasing grazing intensity. Also, the functional divergence and evenness in response to the grazing were less responsive. Stable rangelands can be achieved through interventions such as soil fertility, but this study dealts with only a better understanding of the total functional characteristics of rangeland species. Our results showed that soils from low grazing have higher nutrient concentration than other intensities. Trapping by livestock can lead to congestion and changes in levels of infiltration, bulk density and reduced destructive activities (Yu and Jia, 2014). Moreover, under long-term pressure of grazing, some energy and nutrients are transmitted to the diet (Lu et al., 2015; Zuo et al., 2016), while shrublands can collect a large amount of soil organic matter due to the increase of litter on the soil surface by the lowering of bed decomposition (Nieder and Benbi, 2008). This could be the consequence of the reduction segregation of the nutrient concentration among habitats.
References
Baize, D., 2000. Guide des analyses a pedologie. INRA, Paris.
Bates. D., Maechler, M, Bolker, B., 2011. lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-38.
Casanoves, F., Pla, L., Di Rienzo, J.A., Sandra, D., 2011. F Diversity: a software package for the integrated analysis of functional diversity. Methods in Ecology of Evolution 2, 233–237.
Chillo, V., Ojeda, R. A., Capmourteres, V. M., 2017. Functional diversity loss with increasing livestock grazing intensity in drylands: the mechanisms and their consequences depend on the taxa. Journal of Applied Ecology 54, 986-996.
Cingolani, A, M., Noy-Meir, I., Díaz,S., 2015. Grazing effects on rangeland diversity: a synthesis of contemporary models, 15( 2) , 15(2):757-773
Cornelissen, J. H. C., Lavoral, S., Garnier, E., Diaz, S., Buchmann, N., Gurvich DE, Reich P B, Steege, H., Morgan, H. D., van der Heijden, M.G. A., Pausas, J. G., Poorter, H., 2003. A handbook of protocols for standardized and easy measurement of plant functional traits worldwide. Australian Journal of botany 51, 335–380.
De Bello, F., Price, J.N., Münkemüller, T., Liira, J., Zobel, M., Thuiller, W., Gerhold, P., Lavergne, S., Leps, J., Zobel, K., Pärtel, M., 2012. Functional species pool framework to test for biotic effects on community assembly. Ecology 93, 2263–2273.
Dubuis, A., 2013. Predicting spatial Patterns of Plant Biodiversity: from Species to Communities. University of Lausanne, witzerland, Thesis PhD, pp. 295
Dwyer, J. M., Hobbs, R.J. Mayfield, M. M., 2014. Specific leaf area responses to environmental gradients through space and time. Ecology 95, 399–410.
Friendly, M. and Fox, J., 2013. Visualizing generalized canonical discriminant and canonical correlation analysis. R Package ‘‘candisc’’, version, 0.6–5
Heidari, GH., Saeedi Garaghani, H. R., 2013. Compare changes in species richness and diversity and life form in utilization sites on the southern Damavand mountain rangelands. Journal of Rangeland Watershed 66 (4), 535- 547. (In Persian).
Jafarian Z, Kargar M, Tamartash R, Alavi SJ. 2019. Spatial distribution modelling of plant functional diversity in the mountain rangeland, north of Iran, Ecological Indicator 97, 231-238.
Jafarian, Z., Ahmadi, F., Kargar, M., 2018. Effects of grazing intensities on functional diversity and species diversity indices in the Bolban Abad rangeland, Kurdistan province, Iranian Journal of Range and Desert Research 24 (4), 768–777. (In Persian).
Jäschke,Y., Heberling, G., Wesche, K., Environmental controls override grazing effects on plant functional traits in Tibetan rangelands. 2020. Functional Ecology34:747–760. doi.org/10.1111/1365-2435.13492.
Jost, L., 2006. Entropy and diversity. Oikos 113.363–375.
Karadimou, E., Tsiripidis, I., Kallimanis, A.S, Raus, T., Dimopoulos, P., 2014. Functional diversity reveals complex assembly processes on sea-born volcanic islands. Journal of vegetation Science 26, 501-512.
Kraft, N., Valencia, R., Ackerly, D., 2008. Functional traits and niche-based tree community assembly in an Amazonian Forest. Science 322, 580–582,
Laliberte, E., Shipley, B., 2010. Functional diversity: measuring functional diversity from multiple traits, and other tools for functional ecology. R package version 1.0-9.
Lu, X., Yan, Y., Sun, J., Zhang, X, Chen, Y., Wang, X., Cheng, G., 2015. Short-term grazing exclusion has no impact on soil properties and nutrients of degraded alpine grassland in Tibet, China, Solid Earth. 6, 1195–1205. https://doi.org/10.5194/se-6-1195-2015
Mansoori, Z, Tahmasebi, P, Saeedfar, M, Shirmardi, H.A., 2013. Answer diversity of plant communities to grazing during the tilt-shift function is to protect the steppe and semi-steppe zones. Environ. Protection plant 1(3), 91-104.
Mason, N.W., Richardson, S.J., Peltzer, D. A., de Bello, F., Wardle, D.A., Allen, R. B., 2012. Changes in coexistence mechanisms along a long-term soil Chrono sequence revealed by functional trait diversity. Journal of Ecology 100, 678–689.
Moghadam, M. R., 1998. Rangeland and range management. Publication University of Tehran, 470 p.
Mouchet, M.A., Villeger, S., Mason, N.W. H., Mouillot, D., 2010. Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules. Functional Ecology 24, 867–876.
Nieder, R., Benbi, D.K., 2008. Carbon and Nitrogen in the Terrestrial Environment, Springer Science 159 P.
Niu, K., He, J. SH., Zhang, S.H., Martin, J., Lechowicz, Z., 2015. Grazing increases functional richness but not functional divergence in Tibetan alpine meadow plant communities. Biodiversity Conservation 2, 1-12.
Olff H. and Ritchie M E. 1998. Effects of herbivores on grassland plant diversity. Trends Ecology &Evolution 13, 261–265.
Omidipour, R., Tahmasebi, P., Faizabadi, M.F., Faramarzi, M., Ebrahimi, A., 2021. Does β diversity predict ecosystem productivity better than species diversity? Ecological Indicators, 122, 107212.
Pellissier, L., Pottie, J., Vitto P., Dubuis, A., Guisan, A., 2010. Spatial pattern of floral morphology: possible insight into the effects of pollinators on plant distributions. Oikos 119, 1805–1813.
Petchey, OL., Gaston, K. J., 2006. Functional diversity (FD), back to basic and looking forward. Ecol Lett 9, 741-758.
Rahmanian, S., Hejda , M., Ejtehadi ,H., Farzam, M., Memariani,F., Pyšek,P. 2019. Effects of livestock grazing on soil, plant functional diversity, and ecological traits vary between regions with different climates in northeastern Iran, Ecology and Evolution 9: 8225–8237.
Ricotta, C., Moretti, M., 2011. CWM and Rao’s quadratic diversity: a unified framework for functional ecology. Oecologica 167,181–188.
Rossier, L., 2011. Predicting Spatial Patterns of Functional Traits. MS.c thesis. University of Lausanne, Switzerland, p. 44
Simova, I., Violle, C., Kraft, N. J., Storch, D., Svenning, J.C., Boyle, B., 2014. Shifts in trait means and variances in North American tree assemblages: species richness patterns are loosely related to the functional space. Ecography 38, 649-658. doi: 10.1111/ecog.00867
Spasojevic, M. J., Suding, K. N., 2012. Inferring community assembly mechanisms from functional diversity patterns: the importance of multiple assembly processes. Journal of ecology 100:652–661.
Tahmasebi, P., Moradi, M., Omidipour, R., 2017. Plant functional identity as the predictor of carbon storage in semi-arid ecosystems. Plant Ecology & Diversity, 10(2-3), 139-151.
Teague, R., Barnes, M., 2017. Grazing management that regenerates ecosystem function and grazingland livelihoods. African Journal of Range & Forage Science, 34(2), 77-86.
Yu, Y., Jia, Z.Q., 2014. Changes in soil organic carbon and nitrogen capacities of Salix cheilophila Schneid along a revegetation Chrono sequence in semi-arid degraded sandy land of the Gonghe Basin, Tibet Plateau. Solid Ear. 51,045-2014. DOI: 10.5194/sed-6-2371-2014.
Villeger, S., Mason, N.W.H, Mouillot, D., 2008. New multidimensional functional diversity dices for a multifaceted framework in functional ecology. Ecology 89, 2290–2301.
Zhang, J. T., Linfeng, J. X., 2015. Affiliated with College of Life Sciences, Beijing Normal University Variation of plant functional diversity along a disturbance gradient in mountain meadows of the Donglingshan reserve, Beijing, China. Russian of Ecology 46 (2), 157-166.
Zuo, X., Zhou, X., Lv, P., Zhao, X., Zhang, X., Xiyuan, W., Yue, X., 2016.Testing Associations of Plant Functional Diversity with Carbon and Nitrogen Storage along a Restoration Gradient of Sandy Grassland, Frontier Plant Science 7, 189.
تغییرات تنوع گونهای و کارکردی گیاهان تحت شدتهای مختلف چرای دام در مراتع استان مازندران، ایران
چکیده
بین شاخصهای تنوع کارکردی مانند غنای کارکردی، واگرایی کارکردی و یکنواختی کارکردی تفاوت وجود دارد که میتواند به ارائه درک واضحتر و کاربردیتر از رابطه بین تنوع گیاهی و اکوسیستم عملکرد کمک نماید. بنابراین این تحقیق با هدف بررسی تغییرات تنوع گونهای و تنوع عملکردی تحت شدتهای مختلف چرای دام در مراتع چنگیزچال در استان مازندران انجام شد. در بهار و تابستان سال ۱۳۹۳، سه ویژگی کارکردی شامل سطح ویژه برگ (SLA)، ارتفاع گیاه (VH) و محتوای ماده خشک برگ (LDMC) در سه شدت چرایی (کم، متوسط و زیاد) مورد اندازهگیری قرار گرفت. تنوع گونهای با استفاده از شاخصهای تاکسونومیکی شامل غنای گونهای، شاخص شانون، شاخص سیمپسون و شاخص یکنواختی گونهای اندازهگیری شد. همچنین، تنوع عملکردی با استفاده از شاخصهای مبتنی بر یک ویژگی (FDvar) و شاخصهای مبتنی بر چند ویژگی (غنای عملکردی (FRic)، واگرائی عملکردی (FDiv) و یکنواختی عملکردی (FEve)) اندازهگیری شد. نتایج نشان داد که غنای عملکردی با غنای گونهای در شدت چرای متوسط افزایش داشتند. تنوع عملکرد ارتفاع گیاه بصورت معنیداری در شدت چرای کم افزایش یافت؛ درحالی که تنوع عملکرد سطح ویژه برگ در شدت چرای متوسط بیشترین مقدار را دارا بود. بر اساس نتایج، تنوع کارکرد سطح ویژه با مقدار نیتروژن و فسفر خاک رابطه مثبتی داشتند. هم چنین شدت چرای دام باعث کاهش معنیداری کربن و فسفر خاک در سطح 5 درصد شد. نتایج بیانگر این مطلب بود که چرای دام در مراتع چنگیزچال موجب افزایش رقابت برای کسب نیتروژن و فسفر خاک میشود؛ در نتیجه غنای عملکردی در جوامع گیاهی چرا شده افزایش می یابد. مطالعه حاضر اهمیت بالقوه شدت چرای کم تا متوسط را در تعدیل و کاهش رقابت بین گیاهان برای بدست آوردن منابع غذایی آشکار ساخت.
کلمات کلیدی: تنوع زیستی، پایداری مرتع، مدیریت چرا، ویژگیهای عملکردی برگ، اکوسیستم مرتعی
