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Impact Of Salmon Sourced Nitrogen On The Number Of Stomata In Salmonberry (Brambles)

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Abstract

It is assumed that some species of Salmon is a rich source of nutrients for the nearby plants of any water bodies like (stream, lakes, river etc). After the spawning period, these salmons died and their remains are the rich source of Nitrogen for the plants. Experiment was conducted in the North America on various streams where the Salmonberry plant was selected. The main objective was is to assess the effect of Nitrogen on the Stomatal Density of the leaves of above mentioned plant. Sample was collected and observed in contrast with the following predictors like salmon density, plant canopy, distance of plant from streams, width of stream and length of spawning period.

Keeping in view all of these the predictions were made before taking the samples that either there will be the direct effect of the Salmon density in the streams on the Stomatal density of the leaves of Salmon berries or there will be an indirect effect with a collective aspect of one of the other variables like the role of Canopy cover of the Plant. Soil Moisture percentage can also be a vital part of the transfer of nutrients from water to the plant and it can also be a predictor against the hypothesis that there will be an effect of soil moisture in the stomatal density. Moreover, the distance of the plant can also be the predictor that higher the distance less approach of water to the plant and ultimately low soil moisture. 2 leaves per plant and 15 plants per stream was observed as a sample. More the light on the plant canopy more the number of stomata, it is also predicted in the hypothesis. The data in below confirmed that the stomatal density increases with the increase in the number of carcases of Salmon.

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Introduction

Several species of Salmon are available in the most of the waters around the World, more specially in the North America where the salmon fish is use as a source of meat by both animals and plants specially the polar bears. These fishes after spawn either go to the nearby oceans or die after spawn. Salmons after laying eggs go the nearby oceans during the fall there they (gain most of their body mass) and come back for spawn in the rivers. The dead carcasses of these species are enriched with the several nutients most likely Nitrogen which is a good source for the terestrial plants. Salmon carcasses wash up along the banks of spawning streams and are deposited inland by scavengers and by floods (Ben -David et al. , 1998). Pacific salmon deliver an enormous nutrient addition from the sea to coastal forests of western North America (Mathewson et al. , 2003), and provide a well -studied ecosystem subsidy. Nitrogen (N) is the element required in largest amounts by plants: about 1–5% of total plant dry matter consists of N, which is an integral constituent of proteins, nucleic acids, chlorophyll, co-enzymes, phytohormones and secondary metabolites. N2 is only available to plants that are capable of forming symbiosis with N2 -fixing soil bacteria.

Most plants therefore depend on the other N compounds for their growth. Nitrate is also more mobile in the soil than ammonium and therefore more available to plants (Miller and Cramer, 2004). N is highly mobile in the plant that’s why deficiency symptoms show on the younger leaves. Nitrogen also plays role by assimilating several enzymes paly role in the opening and closing of stomata. Nitrogen fixation is done by nitrogen fixing bacteria (cyanobacteria) by means of nodule formation in the roots of plants where they fix nitrogen in the form (NH4) and (N2) after the series of reactions which ultimately taken up by the plant. This nitrogen is primarily bound in the soil collides where it is attached and after by means of some pathway taken up by the plant through roots. Stomata are small pores present in the epidermal cells of leaves in plants. Stomata open at day time and close at night take in carbon dioxide required for the photosynthetic activity during the day. They give out excess water released in the process of respiration during night along with carbon dioxide.

Opening and closing of stomata is controlled by concentration of solute in guard cells regulated by the potassium (K+) ions. Opening of stomata is done by solutes from neighboring epidermal and mesophyll cells enter the guard cells lowering its osmotic potential and water potential. This lowered water potential and osmotic potential will allow movement of water into guard cells from neighboring cells. Guard cells become turgid due to water accumulation in them which results in the opening of the guard cells. During closing, as the stomata open the solute concentration is reduced. This makes the water from the guard cells to move away into neighboring cells. Now, guard cells become flaccid with no water. They collapse against each other and result in the closing of stomata. The carbon dioxide required for photosynthesis is taken up through stomata, while minerals and nutrients acquired in the root system are distributed by the vascular system via capillary action as water is lost through stomata by transpiration (Carlson et al. , 2011; Shabala, 2013). Stomatal density is positively correlated with soil fertility (Frey et al. , 1996; Körner et al. , 1986; Siegwolf et al. , 2001), and with light intensity (Pazourek, 1970; Sáez et al. , Ríos 2012), probably because CO 2 uptake rather than light or nutrient availability limits growth. Stomatal density thus mediates a trade -off between carbon gain and water loss, and plants adjust stomatal density and aperture (Manzoni et al. , 2013) in response to the availability of CO 2, nutrients, light and water – all of which affect the balance between allowable water loss and potential photosynthetic gain (Abrams, 1990; Kolodziejek and Michlewscka, 2015; Manzoni et al. , 2013; Xu and Zhou, 2008).

Salmonberry (Rubus spectabilis) is a common shrub in coastal forests of the Pacific northwest. This nitriphilic plant seems especially well -adapted to exploiting salmon -derived nutrients (Hobbie et al. , 2000) as its abundance and foliar nitrogen are both elevated along streams with larger spawning runs of salmon (Hocking and Reynolds, 2011). Here predicts a positive correlation between the density of salmon and the stomatal density of salmonberry. The test for an effect of soil moisture, but as there are all riparian systems in a wet temperate forest so do not expect water to be limiting and that any effect would be weak. Finally, as salmon -derived nutrients can lead to alterations in the structure of riparian vegetation that affect the light level, and as stomatal density changes positively with light level, we predict an effect on stomatal density by this indirect pathway.

Material and Methods: Study conducted on the 16 streams in the various areas in the North America where the salmon population varies according to the number of species. The main parameters are observed as a result of predictors like D-fromS distance of plant from stream (m), Canopy fraction of canopy cover (%), Stem density number of stems of the plant counted at 10 cm above the ground, Soil moisture volumetric moisture content of the soil (%), Length spawning area length of the stream (m), Stream width (width) of the stream (m), Salmon density total salmon density (kg salmon per meter stream). All these predictors assessed against Stomatal Density (number of stomata per cm2 of leaf), stream by stream. The purpose is to check the direct and indirect influence of these on the stomatal density. The streams of different length and width were selected depending on the distance of them and moreover the salmon density also keep in view (Gregory et al. , 2018).

Collection of leaves from Salmonberry

On each stream we collected two leaves from each of 15 salmonberry plants. Both leaves originated from the same stem. Plants were selected opportunistically along both banks along the length of the spawning reach (range 100-1800 m) within 3 m of the stream bank, though those plants were avoided that had their roots in the stream. Healthy, fully expanded mature leaves collected. As there is likely intra-plant variation in stomatal density depending on height and leaf location leaves from each plant were collected from the same position within a plant (chest height, outer stem). Salmonberry is clonal, with clones in coniferous forests similar to ours typically less than 5 m in diameter. To ensure that leaves were collected from different clones, sample sites were separated by at least 10 m. Each leaf was pressed and dried for at least 3 days before storage (Gregory et al. , 2018). Measured the soil volumetric moisture at the base of each stem using a soil moisture meter with a 12 cm probe (HydroSense CD620, Campbell Scientific Inc. ). Estimated plant density as the number of salmonberry stems within a radius of 1. 5 m around this point. Tappeiner et al. (1991) found two to six clones on 4 m2 plots, so more than one clone may have been involved in the counting of the stems. A canopy measure (% cover) at each collection site, using a densimeter on which 42 points were selected, and converted this to percentage cover (Gregory et al. , 2018). Measurement of StomataStomatal density of each leaf was measured using the ‘nail varnish impression’ method described by Van Den Dries et al. (2013), Geisler et al. (2000), and Kolodziejek and Michlewscka (2015).

As there may be intra-leaf variation in SD, the position of the impression on each leaf was standardized. Clear nail varnish was applied to the bottom (abaxial) side of a leaf not more than 1 cm from the midvein, dried for at least 20 min, and removed using clear tape. The impression was made at the widest portion on the middle of the three leaflets, between the second and fifth lateral secondary veins on each side of and directly next to the main central vein. Photographs of the impressions were taken with a Canon 5D Mark II camera mounted on a Nikon Eclipse 600 microscope equipped with a Nikon plan fluor 20x objective and a Nikon 2. 5x phototube lens using brightfield illumination, recording an image area of 0. 1944 mm2(Gregory et al. , 2018). Multiple focal planes were photographed to generate focused images of the majority of stomata. Images of focal planes were imported into Adobe Photoshop CC, and a black circle was placed on each stoma with each circle on a separate layer. The number of layers with circles represents the number of stomata (Gregory et al. , 2018). Statistical AnalysisThe stomatal density estimate for each stream was made as follows: We made a total of 2432 impression (16 streams, 15 plants per stream, 2 leaves per plant, 2 impressions per leaf). Repeat counts of the same impression were highly correlated and were averaged (table. 1).

Stomatal densities of the matched impressions on each side of the central vein of each leaf were also highly correlated and averaged to give an estimate for that leaf. The estimates of the two leaves per plant were highly correlated. A linear mixed model had used to examine the relationship between stomatal density and salmon density for each stream, keeping in view the canopy cover, stem density, soil moisture, leaf area, the distance upstream of stream mouth, and the distance of plant from stream to the shore. Included leaf area (measured using ImageJ) as there is some evidence that leaf size affects stomatal density (England and Attiwill, 2011; Xu and Zhou, 2008). To represent the sampling structure, a random intercept model, with plant nested within stream as a random effect to correct for spatial dependency and the sampling of two leaves per plant (package nlme; (Pinheiro et al. , 2015; R Studio Team, 2015). No variables were strongly correlated (all r < 0. 4; see Table 2), so all variables as well as all two-way interactions were included in the initial model. We sequentially removed first unsupported interactions and then unsupported main effects. Significance was assessed using likelihood ratio tests.

Order effects were assessed by back-checking the significance of all terms dropped from the model. Equation model used a piecewise structural (SEM; Lefcheck, 2015) to investigate relationships between the variables linking salmon and stomatal density. SEMs are a form of path analysis, with every path representing a hypothesized causal relationship discussed briefly in the previous studies. ResultsSalmon densities varied between 0 and 49 kg salmon per meter of spawning reach length (overall mean=14. 53 kg m-1, SD=12. 0). Soil volumetric moisture ranged from 9-93% (mean=37. 2%, SD=19. 0), with stem density ranging from 2-76 stems (mean= 25. 5, SD=16. 2). Canopy cover ranged from 0. 21-1% (mean=0. 63%, SD=0. 14). Basic correlations between stomatal density and the predicted main effects are summarized in Table 2 and displayed in Figs 1a – d. The final linear mixed model is summarized in Table 3. As predicted, stomatal density varies with salmon density (see Fig. 1a), but the effect depends on soil moisture. At low soil moisture (10%), the main effect plus interaction is equal to -31. 13 + (6. 318*10), whereas at high soil moisture content (90%) the combined effects are equal +464. The model also shows that the density of stomata decreases with canopy cover (Fig), which can say as expected given that stomatal density increases as light intensity increases. Stomatal density varies with stem density (Fig), an effect dependent on soil moisture. These results below interpret that salmon density has an overall positive effect on stomatal density, with the strength of the relationship increasing with soil moisture. The final model shows a strong fit to the data (r2=0. 94), predicting that stomatal density increases from the range of salmon densities among streams, after controlling for the other variables. Stomatal density increases by 2. 21 stomata mm2 with each additional kilogram of salmon per meter of stream.

Discussions

Stomatal density in plant is considered quite responsive in the process of photosynthesis, but it can be alter with the availability of nutrients, light and water. These responses are interpreted as mechanisms whereby a plant adjusts the balance between carbon gain and water loss (required for nutrient transport) to support photosynthetic potential (Gregory et al. , 2018). In this paper predicted that the stomatal density of salmonberry leaves collected along the 16 streams in North America can vary directly with the number of salmon spawning in the stream, reasoning that the more water in these habitats allows stomatal density to be elevated in order to capture the nutrients delivered from salmon carcasses. The comparison of 16 streams confirmed this prediction. However, the fact that soil moisture can alters the relationship between salmon and stomatal density. Apart from that the plants also go for the other nutrients in water when the water is in abundance. Linear model supported the idea that the increase in stomatal density is composed of both a direct as well one or more indirect responses to nutrient enrichment, the latter arising via the effect of nutrient enrichment on canopy cover. Based on different comparisons of the total path coefficients, the direct effect of salmon density on stomatal density is 100 times stronger than any indirect effect.

Effects of soil moisture, leaf area and distances from stream on salmonberry stomatal density are not detectable using our data but there is an effect. Using model, it can also suggest that canopy cover is negatively associated with salmon density. This may be due to associations between canopy cover, salmon density, and other variables such as stream width (wider streams have lower canopy cover), which ultimately reduce the effect of sunlight and also a reverse effect on the stomatal density. Higher light increases photosynthetic potential (Sáez et al. , 2012), and studies show that light intensity and stomatal density are positively related across a broad range (Kong et al. , 2016; Mazzanatti et al. , 2016; Pazourek, 1970; Petrova, 2012; Rozendaal et al. , 2006).

Reversely, the reduced light intensity under a denser canopy can lead to reduce stomatal density, as per results found. Stem density and salmon density are strongly and positively related, an effect also found by Hocking and Reynolds (2011). This and other aspects of the performance of salmonberry in response to salmon nutrient subsidies led Hocking and Reynolds (2011) to confirm that salmonberry is a nitriphilic species. In conclusion, we have found that the nutrients derived from salmon carcasses lead to an increase in stomatal density of salmonberry both directly and through indirect pathways (Gregory et al. , 2018). This provides studies into the way that plants use nitrogen, including physiological processes that lead to correlations between salmon and salmonberry plant composition.

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