This study was done with the aim of evaluating the relation between flora biodiversity and efficiency of six buffer zones according to perimeter, area and width considerations.Six riparian buffer zones were selected andPerimeter, area, width, latitude and longitude were measured. Next, species compositions were investigated in each zone and then, biodiversity indices were calculated in 20×20 m² plots. In addition, soil samples were collected along 3 parallel transects from the beginning to the end of the farm and beginning to the end of six buffer zones at depth of 30 and analyzed for N and P concentrations. A two-way between-groups analysis of variance was conducted to explore the impact of biodiversity and the location of points on levels of N and P reduction.Results of this study showed that the difference between biodiversity indexes, which is primarily due to the diversity of species composition, influences the effectiveness of the "riparian buffer zones"(RBZ).

Keywords: evenness, nitrogen and phosphorus reduction, riparian buffer zone, species composition

The majority of rivers in most countries is isolated from agricultural fields by strips, commonly referred to as RBZ, and is comprised of  narrow areas of natural plants.^1,2 They are considered as unique and dynamic systems³ and act as an economically efficient way to reduce agricultural nonpoint source pollution.^4,5 Agricultural runoff is famous for the potential to transport sediment, nutrients and pesticides,¹ more specifically N and P, to surface water and can affect the environment.⁶ Surface and ground water contamination by N and P from agricultural runoff is a crucial factor influencing water reservoirs all around the world.^7,8 P is known as the most vital nutrient-limiting factor with an ability to induce water pollution.⁹ High concentrations of N in surface waters is also a cause of pollution, and in turn, results in instability of the ecosystem.¹⁰ The effect of RBZ is of great satisfaction, with a reduction of 70– 98% for P and 70–95% for N.^11,12

RBZ, as an interface between land and aquatic ecosystems, has high environmental gradients, ecological processes, and populations.¹³ RBZ demonstrates a complex system of biodiversity, with high numbers of species bound to and interacting within the habitat.¹⁴ They help create a framework for recognizing the biodiversity in flora. They play a role as habitat for resident flora as in other linear patches.¹⁵ In these linear patches, plant species richness indices of ten changes significantly in space and time around stream margins, and these changes affect the biota and processes considerably¹⁶ that effect efficiency of RBZ.

There are so many researches about RBZ from many aspects in the world,^11,17 however, studies about them are limited in Middle Eastern countries and despite the importance of biodiversity in the structure and efficiency of buffer zones, they have not been studied comprehensively. Local researches are necessary to gain information on buffer performance, with particular emphasis on biodiversity of buffers. Thus, this study was done with the aim of evaluating the relation between flora biodiversity and efficiency of six buffer zones according to perimeter, area and width considerations.

Study area

ZayandehRud River Basin is one of the most crucial water bodies in the arid central Iran which has been persistently confronted by water stress in the course of the past 60 years. The ZayandehRud River Basin includes an area of about 26,917 km² in central Iran. The basin consists of six irrigation networks located mainly in the upper sub-basins that provide agriculture, the main water consumer, with water. Its major traditional crops are wheat, rice, barley, and corn, which are highly water consumptive. ZayandehRud River, with an average flow of 1400 million cubic meters (MCM) with 650 MCM of natural flow and 750 MCM of transferred flow, is the main surface water resource of the basin.¹⁸ The river water has drinking, industrial, and agricultural usage. In its west–east journey, Zayandeh-Rood River runs through several agricultural fields.¹⁸ The identification of pollutants throughout the river is vital and has a great impact on controlling the ecological circumstances of the basin. There are many riparian buffer zones along this river. Therefore, six riparian buffer zones were selected according to their differences, due to they are typical representatives of this area. (Figure 1).

Figure 1 Distribution map of the study area.

Overall design

For the evaluation of relation between biodiversity and efficiency of buffering, six riparian buffer zones were selected around Zayandeh-Rood River. No artificial fertilization of the farm was done in these regions. One of these zones (first zone) had more complex species diversity than the other ones. First of all, perimeter, area, width, latitude and longitude of six buffer zones were measured along agricultural land around Zayanderud. Next, species compositions were investigated in each zone and then, biodiversity indices were calculated in 20×20m² plots. In addition, soil samples were collected along 3 parallel transects from the beginning to the end of the farm and beginning to the end of six buffer zones at same depth of 30 and analyzed in laboratory for N and P concentrations in length of 20 m. All of distances in all zones were equal. Moreover, other factors such as soil type were same in all regions. The significance of different samples was tested by two ways between groups ANOVA. When results were shown to be significant, Tukey’s multiple comparison tests were run.

Biodiversity data analysis

The diversity indices of richness, evenness, and biodiversity were evaluated for plant diversity through using the most common methods of their estimation mentioned in previous studies.^19,20 

Richness-Different methods were suggested by many investigators to measure this index and the number of species (n) as the species richness (s) is the most common method among others.^21,22

Evenness-Simpson's evenness index is defined as:

$E_{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$D$}\right.}=\frac{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$D$}\right.}{n}$                  [1]

Where D is Simpson's biodiversity index and n is the number of species. As is the case for Simpson, this method is less sensitive to rare species. Camargo's evenness index is calculated by:

$\dot{E}=1-{\displaystyle \sum _{n_1=1}^n{\displaystyle \sum _{n_2=n_1+1}^n\left|p_{n_1}-p_{n_2}\right|/n}}$                 [2]

Where P_nis species frequency and n is the number of species. Smith & Wilson (1996) suggested a new method that is based on species frequency. This method is sensitive to rare and dominant species of the community. It is measured through the equation:

$E_{\mathrm{var}}=1-2/\pi \arctan \left[{\displaystyle \sum _{n_1=1}^n{\left(\ln \left(x_{n_1}\right)-{\displaystyle \sum _{n_2=1}^n\left(\ln \left(x_{n_2}\right)\right)/n}\right)}^2}/n\right]$                 [3]

Where n₁ is the number of individuals of the first species, n₂ is the number of individuals of the second species, and n is the number of all individuals in all species.

Biodiversity-Simpson is the most common and frequently used biodiversity index.^23,24  This method is measured by:

$D=1-{\displaystyle \sum _{i=1}^n{p}_i^2}$                 [4]

Where n is the number of species and p_i is the relative frequency of each species. The other popular method of biodiversity measurement is Shannon-Wiener. It estimates the average uncertainty in assigning each randomly chosen individual to the species it belongs to. The following equation is applied:

$H^{\prime }={\displaystyle \sum _{i=1}^n{p}_i\ln p_i}$                 [5]

Where n is the number of species and p_i is the relative frequency of each species. The third method of biodiversity estimation is Brillouin. It is similar to Shannon-Wiener and is applied when random selection of samples is doubtful and is defined as:

$HB=1/n\ln n!/n_1!n_2!$                 [6]

Where n₁ is the number of individuals of the first species, n₂ is the number of individuals of second species and n is the number of all individuals in all species.

Monitoring is the key to understand the environmental sustainability and the RBZ efficiency. Therefore, perimeter, area, width, latitude and longitude of six RBZs were measured in agricultural land along Zayanderud. Results showed that the first zone has a larger area and the second zone has a higher perimeter and path length than the other (Tables 1&2). Therefore, in order to conduct a fine comparison of the zones, six20×20 m² plots (400m²) were selected in six mentioned RBZs.

Species compositions

Species compositions were assessed in six zones. Results are shown in Table 2.

Biodiversity indices’ data

Indices were calculated for each zone and the results are shown in Table 3.

Results showed that richness in the first zone (n=5) was higher than that of the other zone (n=1) and evenness in the second zone (1) was higher than that of the first zone (average 0.884) and other zone. Moreover, heteroginity indices were relatively higher in the first zone.

P and N concentrations

P and N concentrations were determined in 3 parallel transects and are shown in Figures 2&3. The results showed that there is significant relationship between the zone-point in all RBZ. This correlation is highest between the first and second zone. The results of measuring the concentration of N and P in soil in the all zones revealed that the highest N and P concentration is related to the end of the farm and the lowest concentration is related to the end of the buffer zone. N and P concentrations in soil in the first zone increased significantly from the beginning of the farm to the end of the farm, and then decreased sharply from the beginning of the buffer zone to the end of it, as average concentration of N and P dropped from 0.33 mg L^-1 to 0.035 mg L^-1, and from 6.97 mg L^-1 to 1.74 mg L^-1, respectively (P value˂ 0.05).

Figure 2 Average concentration of N forms (mg/l) in three parallel transects of six zones in RBZ.

Figure 3 Average concentration of P forms (mg/l) in three parallel transects of six zones in the RBZ.

The average concentration of N and P in soil in the second zone dropped from 1.01 mgL^-1 to 0.07 mgL^-1 and from2.6 mgL^-1 to 0.6mgL^-1, respectively (P value˂ 0.05). The results of the comparison between the six zones indicated that the concentration of N in the first (total=0.968 mgL^-1) zone is less than that of the other zone (total=1.78 mgL^-1) and the concentration of Pin the first zone (total=19.77 mgL^-1) is more than that of the other zone (total=7.61 mgL^-1). (Tables 4&7).

A two-way between-groups analysis of variance was conducted to explore the impact of biodiversity and the location of points on levels of Nitrogen reduction in the RBZ, measured through sampling N concentrations in 5 points in 2 zones. Each zone was sampled in 5 different points (Point 1: Beginning of the Farm, Point 2: Middle of the Farm, Point 3: End of the Farm, Point 4: Beginning of the RBZ, Point 5: End of the RBZ). The interaction effect between the zones and the points was statistically significant, with F=14.092 and p =0.000 (Table 5), which means the different biodiversity indices in the six zones had an effect on the N reduction. There was a statistically significant main effect for points(F = 36.707, p = .000); moreover, the effect size was large (partial eta squared =.880). Post-hoc comparisons using the Turkey HSD test (Table 6) indicated that the mean score for point 1(M = .33500, SD = .073959) was significantly differentfrompoints3 (M = .66833, SD = .417105), and 4(M=.10667, SD=.053200).Point 2 (M = .21333, SD = .077115) did not differ significantly from either of the other points, except for point 3 (M = .66833, SD = .417105). Point 4 (M=.10667, SD=.053200) was significantly different from point 1 (M = .33500, SD = .073959) and point 3 (M = .66833, SD = .417105), but did not differ significantly from point 5 (M = .05250, SD = .027318). Point 5 (M = .05250, SD = .027318), like point 4 (M=.10667, SD=.053200), was significantly different from points 1 (M = .33500, SD = .073959) and 3 (M = .66833, SD = .417105).The main effect for Zone(F= 19.991, p = .000)reached statistical significance with partial eta squared of 0.5, showing a large effect.

A two-way between-groups analysis of variance was conducted to explore the impact of biodiversity and the location of points on levels of Phosphorus reduction in the RBZ, measured through sampling P concentrations in 5 points in 2 zones. Each zone was sampled in 5 different points (Point 1: Beginning of the Farm, Point 2: Middle of the Farm, Point 3: End of the Farm, Point 4: Beginning of the RBZ, Point 5: End of the RBZ). The interaction effect between the zones and the points was statistically significant, (F=3.537 and p =0.024, pvalue<0.05) (Table 8), which means the different biodiversity indices in the six zones had an effect on the P reduction. There was a statistically significant main effect for points (F = 10.665, p = .000); moreover, the effect size was large (partial eta squared = .681). Post-hoc comparisons using the Tukey HSD test (Table 9) indicated that the mean score for point 1(M =2.275, SD =1.002173) was significantly different from points 3 (M =4.785, SD =2.764031). Point 2 (M =2.73333, SD =.982439) did not differ significantly from either of the other points, except for point 3 (M =4.785, SD =2.764031). Point 4 (M=2.72500., SD=2.232396) was significantly different from point 3 (M =4.785, SD =2.764031), but did not differ significantly from point 5 (M =1.17000, SD =.936184). Point 5 (M =1.17000, SD =.936184), like point 4 (M=2.72500., SD=2.232396), was significantly different from point 3 (M =4.785, SD =2.764031). The main effect for Zone (F= 45.980, p = .000) reached statistical significance with partial eta squared of 0.697, showing a large effect.

RBZ differences can create sustainable environment if they evaluate and manage properly. Generally, results showed that N and P were accumulated from the beginning to the end of the farm, as there was a 0.13%and a 0.87% increase per meter for N and a 0.50% and a 26 % increase per meter for P at the first and second zones, respectively. Subsequently, at the start of the root system in the mentioned tree area in the beginning of the RBZ, a 1.38% and a 2.41 % reduction per meter for N concentration and a 0.59% and a 1.15% reduction per meter for P concentration were observed in the first and the second zones, respectively. Eventually, due to the final completion of phytoremediation and integral effect of the root system of trees in the RBZ, a 0.3% and a 0.45 % reduction in N concentration and a 1.45% and a 0.33% reduction in P concentration were seen at the end of the RBZ in the first and second zones, respectively.

Results of this study showed that the difference between biodiversity indexes, which is primarily due to the diversity of species composition, influences the effectiveness of the RBZ. According to Wu et al., 2017 there are significant changes in habitat class level between indices. However, a regular trend cannot be observed among the RBZs. Generally, according to the indexes shown in Table 3, in the first zone, which has lower evenness and higher biodiversity, the effectiveness of RBZ in N removal is 31%, around 22% lower than the second zone with high evenness and low biodiversity. Therefore, it could be assumed that evenness probably has a direct relation with RBZ reduction of Nitrogen. Effectiveness of the RBZ in P removal is almost equal in both zones, and the detailed view of this trend shows that P has a disordered behavior in soil and hence, exact conclusions cannot be drawn. There was a significant difference in the diversity indices values in study done by Singh and Singh (2013) and they claim plant diversity indices as useful parameters for comparison of six communities.

In a study done by Hefting et al.,²⁵ RBZs were introduced as effective approaches for the reduction of N which corresponds to the results of the current study at an approximately equivalent rate. Moreover, Borin et al.,¹¹ presented RBZ as a means to reduce P with a high satisfactory rate. According to the results of soil, it could be suggested that soil has an important role in N and P reduction. Boz et al.,⁸ claimed that the composition of soil microbial community and activity could be altered by appropriate manipulation of the environment in which they live. Moreover, Wu et al.,²⁶ argued that changes of soil bacterial community richness and diversity affect nitrogen cycling of the ecosystem and also had the greatest efficiency on soil amendment .If correctly used, the mentioned approach has the capability to attenuate the extra chemicals effectively.

It could be suggested that the significant reduction of N and P pollutants in the RBZ is, relying on their effective phytoremediation properties, due to the combination of ash (Fraxinusrotundifolia), willow (Salix alba), buckthorn (Elaeagnusangustifolia), poplar (Populusnigra) and mulberry (Morus alba). Fraxinusrotundifolia was one of the most frequent species in this region and numerous ecological and geographical ranges are allocated to it. Moreover, it is available and inexpensive and has effective properties in remediation of N and P and also zinc and copper.²⁷ Salix albais an important economic species and has efficient properties in absorption of N, P, zinc, lead, copper and iron.²⁸ In addition to its phytoremediation properties for oil and gas pollution, Elaeagnusangustifoliais an effective species to halt erosion.²⁹ According to a study done by Minoguea et al.,³⁰ in 2012, Populusnigra, as a fast growing woody plant, has important phytoremediation properties for N and P reduction. Qin et al.,³¹ introduced Morusalba with very strong root systems, high environmental compatibility, affordability, and accessibility, with properties for reduction of copper, zinc, nickel, lead and P. Therefore, it can be suggested that species type and composition plays an important role in the reduction of pollution.^32,33

In order to conduct further research in this area, and to correctly estimate the effect of phytoremediation of different species in an RBZ, it is proposed that phytoremediation of the species found in the RBZ be evaluated in greenhouse conditions for both isolated (individual) and combined sets of the mentioned species.

None.

The author declares there are no conflicts of interest.

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