Succession is the process of change in a vegetation community over time. There are several stages in succession known as invasion; the arrival of species, colonisation; the establishment of species, competition; the struggle for survival and dominance which sees the strongest species survive as they are best-adapted and continue to develop, pushing other species out of the area. Succession can be seen across the pingo, where the vegetation changes from grasses and herbs to shrub and finally trees and woodland. As succession occurs the number and type of species change, as does the complexity of species and vegetation height. From beginning to end the process of succession is known as a sere.
Oxygen is needed by plants for oxidative phosphorylation in respiration. The oxygen is needed to accept electrons from the oxidised hydrogen in the electron transport chain. The oxygen is then reduced to water. The transfer of electrons down the transport chain makes energy available, which is used to convert ADP+Pi into ATP.
Below are predicted graphs for the change in light intensity and water content with distance from the top of the pingo. I predict that with distance form the top of the pingo the light intensity will decrease. This is because the pingo increases in depth and will be more sheltered towards the bottom. The secondary succession, which has occurred in the Common, has allowed trees to dominate the flatter areas of the pingo and around the pingo, which will shade the vegetation growing towards the bottom of the pingo.
With distance away from the top of the pingo the amount of water will increase as the distance between the soil and water table is reduced.
Taking these factors into account I predict that there will be greater species diversity at the bottom of the pingo than the top. This is because the plants will be growing closer to the water table and therefore have less competition for water. Although light intensity will be lower than that at the top of the pingo there will still be some light for photosynthesis. The plants will be sheltered from wind at the bottom of the pingo and therefore water loss by transpiration will decrease. However I predict that the optimum conditions for plant growth will be half way down the pingo where light intensity and moisture content are relatively equal or at their average as opposed to the highest value of water content and highest value of light intensity
When correlated against moisture content and light intensity I expect the graph for species diversity to show a positive relationship as follows
With depth of the pingo the soil moisture values will increase. The light intensity and exposure to wind will decrease, as the plants are sheltered and not on the exposed slope. The species diversity will be affected by these factors. There will be greatest species diversity at the optimum pH for the plants. As Foulden Common is chalk grassland it is expected that most of the plants will be calcicoles and thus be adapted to suit the alkaline soils. The greatest species diversity will be where the soil is the most alkaline, for the species will have adapted to suit the alkalinity and thus grow best in those conditions.
In taking into account the adaptations mentioned above I predict that xerophytic plants will be present where there is a shortage of water. These plants include grasses such as Fescue and plants, which have minimal leaf surface areas such as Ladies Bedstraw. The driest areas are hypothesised to be at the top of the pingo. Rosette plants such as plantains will be present where there is a high light intensity and sufficient space to grow, this is because they take up a lot of room and so increase competition for space. Plants with hairs on their surface such as Mouse-Ear Chickweed and Hoary leaf Plantain will be present where there is a lack of water as the hairs have a function to reduce the rate of transpiration.
Variables: A table of the variables of the investigation
Preliminary Investigation:
A preliminary investigation was carried out on the pingo to be studied in Foulden Common. It is impossible to count every organism in a habitat. Therefore only small areas can be studied in detail; however these areas must be representative of the habitat as a whole. The aim of the preliminary was to establish the sample size, that is, the size of the quadrat to be used to measure the species diversity along the pingo. Secondly the preliminary established the sample number, that is, the number of times the quadrat had to be thrown in each zone to obtain a result that was representative of the area. The number of samples at each station must also be calculated to ensure efficiency during the actual investigation. A profile of the pingo was also created. This was conducted so that the zones to be studied in the actual investigation could be worked out. Zones have to be worked because it is impractical to study the whole of the pingo. Therefore a representative sample of the landform has to be examined and studied.
Apparatus:
50x50 cm quadrat
100m tape measure
10 pegs
2x 2m rules
Spirit level
Method (sample size):
- The 50cm by 50cm quadrat was thrown in the area of land to be studied
- Starting in the top left hand corner the number of different species was found in the first square (5cm2) this was recorded in a table.
- The quadrat size being examined was extended diagonally across, creating quadrats of 10cm2 followed by 15cm2, 20cm2 and so on. The number of different species were counted in each of these quadrats and recorded.
- This was continued until the maximum size i.e. 50cm2 quadrat was used and studied
- This was repeated 5 times and an average taken to improve accuracy of results.
- The results were recorded in a table
Results:
Conclusion:
A graph of the results was plotted and the optimum size of the quadrat found to be 35cm2, because after this point there was minimal change in the different number of species.
Method (Sample Number):
- Two species were chosen to be examined; these were Lesser Hawk Bit and Salad Burnette.
- The quadrat was thrown and the number of squares in which the two species were apparent was counted using the optimum quadrat size (each species was counted in turn i.e. first Lesser Hawk Bit and then Salad Burnette). The quadrat was thrown 15 times in total.
- It is important to note that individual species were not counted but the number of squares the species were found in were recorded and then tabulated.
- The cumulative average for the species was calculated and these figures were plotted on a graph (raw data and graphs can be found in the Appendix)
Results:
An example of the working of the cumulative average is as follows
The cumulative average of Salad Burnette at zone eight would be
(26+27+18+25+19+13+27+29) = 184 =23
8 8
The cumulative averages of both species were plotted on a graph and where they both levelled off was taken to be the optimum sample number. Two species were investigated to improve accuracy of the measurement of sample number.
Conclusion
From the graph it can be seen that both species level off at 12 throws. I therefore plan to do 12 samples in each zone, with a quadrat size of 49cm2.
A profile of the pingo was also created; this was one so that appropriate zones will be studied during the actual investigation.
Method:
- The tape measure was laid out along the pingo
- The first 2m rule was held vertically upwards at 0m.
- The second 2m rule was held at 0.5m distance from the first with the spirit level held in between the two. 0.5m was chosen as the distance between each measurement so that no striking feature of the pingo would be left out of the profile and it would be more representative of the actual pingo.
- When level, the decrease in height between the two 2m rules was noted.
- This was repeated along the profile of the pingo, and measurements taken at 0.5m intervals.
- The results were plotted on graph paper to show a profile of the pingo. This was then used to divide the pingo up into an appropriate number of zones that will be representative of the landform as a whole.
- Zones will be marked using pegs so that they are easily identified.
Conclusion:
The total length of the pingo was 10m. It was decided that at least 9 zones should be studied, as this would give a representative sample across the pingo.
The deepest depth of the pingo was 218m; this was divided by 9 (because there were to be 9 zones) the value was rounded to 25m (depth). The pingo transect was divided at every 25m of depth and the zones calculated.
It was then decided to do a sample at 0m, and so giving a total of 10 zones.
Only one side of the pingo will be studied because of time restraints, and because the investigation is looking at the effect of height not aspect.
Apparatus: the apparatus that will be used to conduct this experiment are as follows
Methods:
At each zone a number of measurements will need to be taken.
i) Species Diversity
- A key of species will be produced looking up species in the pingo in a book of wild plants and flowers. This will be used to identify the plants throughout the investigation
- The quadrat will be randomly thrown in the zone to be studied (starting with zone 0 and working down to zone 9). A random sample was chosen to avoid bias and so the data collected would be representative of the zone as a whole.
- The number of squares each different species is apparent in will be noted
- The quadrat will be thrown once in each zone, before any repeats are taken. 12 repeats should be taken at each zone.
- This raw data will then be processed using the Simpson’s Index, the results will be tabulated and statistical tests used on them to see the significance of the results obtained.
ii) Light Intensity
- The light intensity will be measured at intervals throughout the day to obtain a true representation of the amount of light each zone receives.
- The light metre will be used. It will be placed perpendicular to the ground, at an arms distance away so that it is not shaded in any way.
- The reading will be recorded 5 times at each zone at four intervals, thus obtaining 20 readings for each zone
- These will be averaged and the T-test will be used on them to see whether there is a significant difference in light levels down the pingo.
iii) Water moisture
- Soil samples will be taken at each zone.
- These will be taken back to the lab and weighed
- The soil (in petri dishes) will then be placed in the oven for at least 12 hours
- The dry soil will then be weighed and the percentage moisture will be calculated
iv) pH
- Soil samples will be taken at each zone
- These will be taken back to lab
- A small amount of soil will be placed in a boiling tube and 5ml of deionised water added to the sample
- It will then be shaken for 1 minute
- Universal indicator will then be added to the solution to test its pH
v) Soil depth
- This will be measured if time permits
- The auger will be screwed into the ground until it hits the bedrock
- A soil transect will be formed and will be transferred onto paper to show difference in the depth of the soil.
Risk Assessment:
A table showing the precautions that must be taken in the common whilst collecting data
A table showing the precautions that must be taken in the lab
Minimising Errors and Fair Test:
It is important for the experiment to be a fair test so that the results are as accurate as possible. In the common measure will have to be taken to ensure that the chance of errors are minimised. Ways in which a fair test could be conducted are as follows:
- All data will be collected on the same day. This will reduce the effects of weather on the results and give a fair representation of the environmental conditions of the vegetation in each zone for example; if it is particularly sunny all plants will have exposure to the same light intensity.
- The equipment used both in the common and in the lab will be the same for each recording for example the same light metre will be used for all of the light readings in the common and the same balance will be used in the lab to measure the mass of all of the soil samples. This will ensure that if there is a fault with the equipment it will be consistent throughout the whole practical.
- Do repeats to make the results more reliable and take an average to improve accuracy where possible. This will be the case for light readings, for species diversity however the repeats will be used to work out percentages and the Simpson’s index then calculated using those figures to show species diversity.
- To minimise errors the light readings will be taken at different times in the day and the average taken. This is so that a true representation of the light levels of each zone can be seen, rather than taking all the light readings at one time which may be unusually bright or overcast. If the sky suddenly becomes very overcast light readings will not be taken because the average will be affected and a representative value will not be obtained.
- Do not place the soil samples in the oven until they are all weighed to ensure that each sample has the same amount of time to dry. Thus the time for evaporation to occur will be the same for each soil sample.
- Similarly take out all petri dishes after 12 hours as opposed to taking them out individually and calculating the percentage water, as this will again ensure that each sample has the same amount of time to dry out.
The species diversity will be calculated by looking at the number of different species in each zone. This will be done 12 times randomly in each zone using a 35x35cm quadrat and the number of time a species appears in the squares recorded. Soil samples will be taken in each zone and used to measure the pH of the soil and the moisture content of the soil. Five light readings will also be taken in each zone at 1-hour intervals for four hours resulting in 20 readings altogether, these will then be averaged. Soil transects will also be created using an auger which drills into the ground to see the depth of the soil before the bedrock. Statistical tests will be done on the results to see if they are significant or not. The abiotic factors will be used to explain the species diversity of each zone.
Changes to method: the following changes had to be made to the method of data collection
- The sampling technique changed to save time. Species were counted according to their presence in rows instead of individual squares, therefore instead of examining 49 squares; the individual species were counted in 7 rows.
- The sample number was also reduced to 7 instead of 12, because the original was not a feasible number of samples to take considering 10 zones were being examined.
- To minimise errors light intensity was taken only at three 1-hour intervals instead of four because the sky became overcast suddenly and therefore the results that would have been taken for the last interval would have affected the average and made the investigation unrepresentative.
Results:
All raw data has been included in an Appendix at the end of the project together with tables of processed data showing the working of the Simpson’s Index working out the species diversity of each zone along the pingo.
It must be noted that in working out the species diversity index (Simpson’s Index/SDI) bare ground was not included which accounts for the apparent discrepancy in figures of the table and the figures used in the formula.
A table showing the percentage water in the soil at each zone along the pingo
A table showing the average light intensity at each zone along the pingo
A table summarising the results of the effect of abiotic factors on the species diversity along a pingo
The soil profiles formed are on separate paper as are graphs showing the distribution of water and light along the pingo.
Scatter graphs correlating the abiotic factors with the SDI for each zone have also been included on separate paper.
Two zonation chart graphs have also been drawn to show where each species was found along the pingo. The first shows a presence of above 1% of the species, however as most of the species were present another one was drawn to illustrate more of a trend, this examined the presence of above 3% of each species along the pingo.
Kite diagrams for the predicted species have also been drawn and statistical tests have been done on the data to test its significance and the strength of the relationship, if any was found.
Statistical tests:
Statistical tests were conducted on some of the results. All statistical tests have been done separately, by hand on paper.
These include Spearman’s Rank coefficient on species diversity and distance, species diversity and light intensity and species diversity and soil water content. Spearman’s Rank coefficient was used because it identifies whether or not there is a relationship between two variables. It also tests the strength of the relationship, yielding numbers, which are either positive or negative showing a positive and negative relationship respectively. The closer the test statistic yielded is to 1 or –1 the greater the strength of the relationship thus the greater the significance of the relationship. In using this test the relationship between distance and the species diversity was tested, as was the relationship between the abiotic factors and species diversity.
The t-test was used on light intensity. This test was used because it tests the difference between two sets of data. The mean of two sets of data can be compared. The test was used to compare the data collected from zone 0 (the top of the pingo) and zone 9 (the bottom of the pingo) thus the test showed whether or not there was a significant difference in the amount of light from the top of the pingo to the bottom.
The chi-squared test was used on data for soil moisture content and for five species: Buttercup, Hoary Leaf Plantain, Ladies Bedstraw, Mouse-Ear Chickweed and White Leaf Clover. This test was used because it tests observed data to the theory that there should equal number of species and an equal amount of moisture along the pingo, this is the ‘expected’ number.
Results of the statistical tests:
A table summarising the outcomes of the statistical tests
Conclusion:
The pingo, on the whole, was very diverse in vegetation. The SDI values yielded high results thus illustrating that the pingo sustained wide variety of plant growth. The SDI increased steadily until zone 4 where it appeared to peak at 16.93. Zone 5 saw a decrease in the SDI and yielded a value of 15.94, zones 6 and 7 increased in diversity from zone 5 however the values were still lower than the SDI of zone 4. Zone 8 again saw a decrease in the diversity to a value of 15.30 (even lower than that of zone 5). Zone 9 exhibited the greatest diversity and had an SDI of 17.02. This supported the hypothesis to an extent, for it was hypothesised that the species diversity would be greater towards the bottom of the pingo rather than at the top of the pingo. However the optimum zone predicted was half way down the pingo where there was a compromise between light intensity and water, whereas the data collected illustrated that the highest diversity was at the bottom of the pingo. The spearman’s rank statistical test conducted on distance and SDI illustrated that there was significant relationship between the distance along the pingo and SDI. The abiotic factors studied should explain this outcome. It must be noted that the pH did not vary across the zone and so cannot be said to have had an effect on the vegetation growth.
Zone 4 had the second highest SDI and so the hypothesis was not completely wrong. The relatively high SDI could be explained because the zone it had sufficient light and water, being roughly half way up the pingo. The fact that it had a thinner layer of soil could explain why didn’t have highest SDI. Having a thinner soil reduces the nutrient-holding capacity of the soil. Zone 9 had the highest SDI despite having one of the lowest light intensity, it had great amount of water it also had a relatively thick soil layer. The SDI illustrated that there was greatest diversity in zone 9, however there was also the greatest number of species here, with little bare ground. The more plants in an area result in more decay and therefore a thicker topsoil and humus layer. It is the thickness of the humus and soil, which hold nutrients, and so zone 9 had many nutrients and thus a larger carrying capacity to hold more plants. The high SDI could also be accounted for in zone 9 because it is relatively sheltered from wind, resulting in less soil erosion (little soil is bare and therefore little soil is exposed and so soil quality is better) but also less transpiration would occur and so plants would not have to be as adapted to water shortage and would not have to have xerophytic adaptations to survive there. Zones 5 and 8 saw a decrease in SDI. This could be because parallel to these two zones were two trees growing. The trees would have taken up water and most on the nutrients from the soil thus reducing the soil quality and amount of nutrients for other species. Zone 8 also had a low light intensity at 0.9 lux; this coupled with soil water content of 19.73% yielded a low species frequency. This in turn would reduce the carrying capacity of the two zones. Zones 6 and 7 see a recovery of the diversity however they are still lower than the SDI of zone 4 again this could be because of water shortage due to the trees in the zones before and after them.
From the line graph showing soil water content along the pingo, it is evident that the general trend is that water content increases with depth of the pingo, thus supporting my hypothesis. This was expected because with distance form the top of the pingo, the depth increased. With increasing depth the soil would be closer to the water table, which is the level at which constant water appears naturally in the ground. Soil depth is another factor, which affects the soil moisture content. Chalk grasslands are a rendzina soil. They are therefore very thin and the bedrock is not far below the top layer of soil. The bedrock is chalk, which is very porous and well drained. The water-holding capacity is largely dependent on the thickness of the soil layer because only the soil can maintain water. From the soil profiles it can be seen that the soil was thinnest on the slope of the pingo at zone 5 this is evident because the chalk appears very high up in the profile, at zone 0 it was thickest with no chalk present at the same depth as the other zones and zone 9 had the intermediate thickness of soil. It would therefore be expected for zone 0 to have the greatest moisture content because it had the thickest soil, however the line graph for light intensity shows that there was greatest intensity of light at the top of the pingo and so the greatest amount of transpiration and water loss would occur there. The zones furthest from the top (i.e. the deepest areas of the pingo) had the lowest light intensity and therefore there would be the least amount of transpiration and evaporation form these zones because of less direct sunlight and thus conserve water.
Soil depth is important because the deeper the soil the more water it will be able to hold. The soil depth will be thickest where there are most plants. This is because as the plants die, they decay to produce humus and improve the quality of the soil. Some areas will be shallower than others due to compaction of soil by both humans and the grazing animals. The soil quality will also be enhanced due to the presence of cattle and rabbits grazing on the land. Cattle graze at the bottom of the pingo, which could explain zone 9 had the highest SDI. They add nitrate to the soil as they excrete which decomposes to form ammonium in the soil. The process of nitrogen fixation by rhizobium, lightning, free living bacteria in the soil convert nitrogen in the air into organic nitrogen in the soil, which decomposes to ammonium. This ammonium is the nitrified by nitrosomonas and nitrobacter in the soil forming nitrates which are then taken up by plants. However grazing also has the effect of trampling the vegetation, and prevents the process of succession. In effect it will reduce the species diversity of an area. Compaction reduces the amount of air in the soil, therefore trampling would reduce the species diversity of an area by reducing the carrying capacity of the soil. Oxygen is needed by plants for oxidative phosphoryllation in respiration. The oxygen is needed to accept electrons from the oxidised hydrogen in the electron transport chain. The oxygen is then reduced to water. The transfer of electrons down the transport chain makes energy available, which is used to convert ADP+Pi into ATP.
Light intensity also supported the hypothesis in that in generally decreased with distance from the top of the pingo. This was expected because the top of the pingo was more exposed to direct light than the zones at depth. The zones at depth were more sheltered and because they were further along succession could be seen to have taken place and taller plants and trees were growing towards the bottom of the pingo. These more complex plants would have shaded the area by intercepting the light. Therefore less light would have reached the vegetation growing at depth.
The scatter graph correlating the SDI and light intensity of each zone illustrated a negative correlation. This means that the lower the light intensity the higher the SDI. This was not expected for light is essential to photosynthesis, which is in turn necessary to plant growth. This was enforced by the Spearman’s rank statistical test, which yielded a value of –0.66 thus illustrating, that there was a strong negative relationship between light intensity and SDI (5% significance level). A T-test was conducted on the light intensities for zone 0 and zone 9, to see if there was a significant difference in the light intensity at the top of the pingo and at the bottom of the pingo. The test showed that there was a significant difference in the light intensity between the top and bottom of the pingo. However the spearman’s rank illustrated that there was a negative relationship. This could be because higher up the pingo the vegetation is more exposed to wind and therefore transpiration. This in turn means that the plants there would have to be adapted to areas with low water and high transpiration rates. This in turn would reduce the species diversity, as not that many species would be able to survive in those harsh climatic conditions.
Light is vital for plant growth. It is necessary for photosynthesis. Plants, being autotrophs are producers. They therefore make up the initial stages of food chains, producing their own food and energy by photosynthesis. W D Phillips and T J Chilton, in A-Level Biology define photosynthesis as “the process by which green plants trap light energy from the sun and transform it into chemical energy stored in molecules of carbohydrate”, whereas Jones and Gregory in Biology 2 further define it as “the fixation of carbon from carbon dioxide into organic molecules using light energy”. Plants therefore require sunlight in order to photosynthesis and produce its own food.
Sunlight of the appropriate wavelength is absorbed by the photosytems within the thylakoid membranes of the chloroplast. Light of 680nm is absorbed by photosystem II and light of 700nm is absorbed through photosystem I. The photons of light are funnelled onto the ‘reaction centre’. The main use of light in photosynthesis is in the ‘light stage’ where it is used in the photolysis of water. Photosystem II contains a water splitting enzyme which together with the energy from sunlight, split water into 2H+, 2e- and ½ O2. Energy from sunlight is then used to boost the electrons to higher energy levels, both in photosystem II and photosystem I. After being initially boosted to a higher energy level (at photosystem II) the electron is accepted by an electron acceptor. It then travels to photosystem I, as it does the electron is passed through a series of electron carriers. The energy lost by the electron in the carrier system is captured by converting ADP and an inorganic phosphate into ATP. Thereby converting light energy into chemical energy. Photosystem I then uses light on 700nm to boost the electrons to a higher energy level, are accepted by an electron acceptor, some then take part in cyclic phosphoryllation whilst other electrons combine with 2H+ (from the photolysis of water) to form 2H, which is then used to reduce NADP. Sunlight will therefore have a substantial impact on the species diversity of an area. The more sunlight there is, the greater the rate and amount of photosynthesis and growth. Therefore the higher the light intensity the greater the species diversity. There will be both interspecific and intraspecific competition for light, which will effect, which plants grow in which areas along the pingo.
The scatter graph correlating water content of the soil with SDI showed no correlation this was verified by the spearman’s rank test done on the data in which the null hypothesis was accepted, that there was no significant relationship between the water content and SDI. This could be because capillary action with rendzina (chalk) soils allows water to be drawn up by plants roots, therefore plants may get sufficient water for growth. However the chi-squared test done on the data showed that there was a significant difference in the amount of water at the different zones along the pingo. This in turn illustrates that the water content itself was not the only factor to affect the SDI however the amount of moisture in the soil will have some affect on the species diversity of the zones.
Water is essential for plant growth and sustenance. It is used in photosynthesis along with sunlight. A thin film of moisture surrounds all soil particles. Water enters the plant root by osmosis. The soil, whilst has some inorganic ions has them dissolved in water, having a diluted effect. The root cell sap and cytoplasm however, have many inorganic ions, which is relatively concentrated thus lowering the water potential inside the root. Water therefore moves down the gradient into the roots by osmosis. The roots have root hairs, which are long thin extensions, increasing the surface area of the root in contact with the soil, and thus in contact with the water. The more water there is in the soil the greater the rate of osmosis will be. Chalk grasslands however are very porous and contain little water. The amount of water is dependent on the depth of the soil layer (on top of the bedrock). If the soil layer is thin the water will drain through it easily, quickly, and run straight through the chalk. If the soil layer is thick, on the other hand the soil will have a greater capacity to hold water, before it is drained through the chalk. Pingoes are glacial features, which occur by the uplift of the land and subsequent collapse of a mound. As a result the base of the pingo will have greater moisture content because the soil is closer to the water table. The ‘water table’ is the level at which there is naturally occurring water in the soil. The higher up the pingo you go, the smaller the amount of water because the soil and bedrock have been lifted up and away from the water table.
Kite diagrams were drawn alongside two zonation chart graphs to show where certain species appeared along the profile of the pingo. One of the zonation chart graphs shows the presence of 1% of a species however this did not show a very clear pattern and so a second zonation chart graph was drawn illustrating presence of above 3% of a species to show greater variation. The zonation chart graph was helpful in showing the progression of succession as it is evident that the number and complexity of species increased with distance form the top of the pingo, for example jointed rush was only found in zone 9 where there was enough water and the soil was thick enough for anchorage and growth. Overall the species diversity was very high throughout the pingo, eight of the species were present in (over 3%) in all of the zones. Other species however are only present at the top of the pingo, such as Ladies Bedstraw; whilst some species are only present towards the bottom of the pingo these include Mouse-ear Chickweed and Buttercup. Species diversity’ is a measure of the different species of vegetation found in an area. The amount of different species in an area is dependent on various factors. The main factor affecting species abundance is the carrying capacity of the environment. Carrying capacity is “the maximum size of a population that can be supported sustainably in a particular habitat” (Cambridge, Biology 2). The carrying capacity is not a set level and fluctuates with the population level of a species. A population will flourish if the carrying capacity is high and will fall if the carrying capacity decreases.
The carrying capacity is controlled by several abiotic factors combined with biotic factors. Biotic factors include competition, density and predation. It also includes and amount of waste produced by the populations, however this is not really applicable to vegetation. Abiotic factors include temperature, light intensity, topography, and edaphic factors (moisture content, pH, depth, organic content and compaction).
The reason for the high diversity along the pingo is because of the soil type. Chalk grasslands rarely see domination of species, as the environment is so diverse, this results in many species adapted to the different conditions. All of the species are calcicoles and are adapted to the high level of calcium carbonate in the soil. There is therefore a lot of interspecific competition restricting succession to a certain extent.
Succession is the process of change in a vegetation community over time. There are several stages in succession known as invasion; the arrival of species, colonisation; the establishment of species, competition; the struggle for survival and dominance which sees the strongest species survive as they are best-adapted and continue to develop, pushing other species out of the area. Succession can be seen across the pingo, where the vegetation changes from grasses and herbs to shrub and finally trees and woodland. As succession occurs the number and type of species change, as does the complexity of species and vegetation height. All ecosystems are subject to intraspecific competition within a species and interspecific competition between species. The species will compete for space, light and nutrients amongst other things. Both types of competition will affect the species diversity and abundance along the pingo. As the density of vegetation increases and the roots take up most of the nitrates and water, the carrying capacity for each population will decrease. As this happens the environment will no longer be able to sustain as many species and they will begin to die. It is this competition that leads to adaptations in plants so that they are best suited to survive in specific conditions.
In looking at the zonation chart graphs and the kite diagrams it is easy to see that certain plants have adapted to grow in certain conditions. Where the soil is thin and water scarce, the vegetation will adapt to reduce water loss by transpiration. Transpiration occurs from the plant leaves to the air. The walls of the mesophyll are wet; some of this water evaporates into the air spaces in the mesophyll layer until they are saturated. The water diffuses out of the stomata travelling down a water potential gradient, as the inside of the leaf is more saturated than outside. Grasses/xerophytes such as Fescue and Spring Sedge are adapted to dry conditions, they curl inwards to create a humid microclimate and protection against wind and therefore reduce transpiration. This could explain why it reduced in abundance down the pingo. From the soil profiles and water content measurement it was evident that the soil was driest higher up the pingo, where fescue was found in abundance as shown by the kite diagram. However the grasses were present throughout the pingo, this could be because England had experienced a long hot summer, this coupled with the fact that the south-facing slope was studied (i.e. the side with oncoming sunlight) could have increased the rate of transpiration and evaporation, leaving the soil drier than it would normally and encouraging the growth of grasses. Another adaptation of these grasses is that their growth tip is in the root not in the shoot and so they don’t stop growing once grazed on unlike other plants, they are therefore able to survive in areas, which are grazed which explain their relatively abundant presence throughout the pingo.
Other adaptations include hairs on the surface of the plant insulate the plant therefore protecting it against wind and reducing transpiration, Mouse-ear Chickweed exhibits this adaptation and was found mostly from zone 3 onwards. The percentage of Mouse-ear Chickweed peaked in zone 3, which is odd because zone 3 had a relatively high water content, however the xerophytic qualities could have caused an increase in transpiration rate and so water loss by transpiration could have balanced out the effect of the increased amount of water. A chi-squared test was done on the distribution of Mouse-ear Chickweed in which the null hypothesis of there being no significant difference in the distribution of the species along the pingo was disproved. Therefore it can be said that this species was found most abundantly where there was a shortage of water i.e. zones 3-7. These zones had the thinnest soil layer and so water would drain through the porous bedrock.
The roots of plants also therefore have to be adapted to the ecosystem. If there is insufficient water the roots will have to be adapted to find water and compete with the other species in the environment for it. The general adaptation for this can be seen in the root hair. The root hair is ‘very thin extension of the cells that make up the outer layer or epidermis of a root’ (Cambridge, Biology 1). They increase the surface area of the root with the soil, so more water can be taken into the plant by osmosis. However other adaptations also occur in certain plants, for example, in dry areas plants are found to have long taproots, which grow deep into the soil in search of water. Thus they grow towards the water table, where there will be greater water availability. Roots also branch across nearer the surface of the soil where they can quickly uptake moisture from precipitation. An example of this is spring sedge where roots branch across from each tuft of grass to the next. Jointed rush also grows towards the bottom of the pingo as shown by the …. Graph. This is because it has long taproots that may reach into the water table. It can only grow at the bottom of the pingo because the soil needs to be thick enough for adequate anchorage of the plant. Therefore as hypothesised taller plants are only apparent towards the bottom of the pingo where soil is relatively thick.
From the kite diagram for Salad Burnette it is evident that it grew mostly in the upper part of the pingo and again at the bottom, with level falling in zones 3-7. Salad Burnette has very thin leaves making it easier for light to penetrate fully through the leaves. Whilst it is known to grow on damper sites, it has long roots, which can penetrate into the soil in search of water which could explain why it is apparent in the drier upper zones and then again in the damper lower zones where the soil is thick enough for the roots to penetrate in search of water. Zones 3-7 however have shallower soil and so water would not be sufficiently available explaining the decrease in the number of species found there. Salad Burnette is therefore present where there is high light intensity, not necessarily high water content because the roots can reach deep into the soil to obtain water. Buttercup proved (in the statistical test) to have significance in its distribution. It was hardly present at all in the upper zones, however was found abundantly towards the bottom (kite diagram). This is because it needs a lot of water to grow. The leaves are very large and so subject to great transpiration. This is reduced by it being at the bottom of the pingo, which is more sheltered and has a lower light intensity to cause a fast rate of transpiration thus conserving water.
The leaf structure of plants is adapted in order to penetrate the most sunlight. The upper layer of cells, the epidermis (which is coated by a waxy cuticle) is a colourless layer of closely fitting cells. It contains no pigment and therefore sunlight is allowed to pass through without interruption. The palisade mesophyll is the next layer. The palisade cells are vertically arranged and are again closely fitting so that the rays of light are fully penetrated by the chloroplasts in the cell. The palisade cells have many chloroplasts, containing chlorophyll in the cell cytoplasm. These trap then sunlight for use in photosynthesis. The spongy mesophyll contains many air spaces for gaseous exchange, i.e. for CO2 to reach the cells for photosynthesis and for O2 to be used in respiration and excess to leave via the stomata.
The leaves of different plants vary greatly. The greater the surface area the greater the amount of sunlight will be able to be absorbed by the leaf. Therefore plants with large leaves will have an advantage over those with smaller leaves for they have a larger surface area to absorb sunlight.
Ladies bedstraw has thin spike-like leaves. Each leaf therefore has a small surface area and so transpiration cannot efficiently occur. Ladies Bedstraw is adapted to conditions of water shortage. This is evident from the kite diagram of its distribution, which illustrates that it is mostly present in the upper parts of the pingo the chi-squared test showed that there was a significance in the distribution of the species. The upper zones are furthest from the water table and so have less water in the soil. Because of its small leaves it has to grow in zones of high light intensity in order to attain sufficient light for photosynthesis, which again explains its presence in the upper parts of the ping as they are most exposed to light. The upper parts of the pingo are also most exposed to wind, however the spike-like leaves reduce the surface area for transpiration to occur and so conserve water. This supports the hypothesis, in that it has xerophytic features and is present where there is a shortage of water i.e. in the upper zones.
White leaf Clover and Hoary leaf plantain both showed to have significance in their distribution in the chi-squared test conducted on them. These two species show similar patterns in that they are relatively evenly distributed in the zones 0-6 and then increase from zones 7-9. Both these plants have a rosette structure. These give them trample-resistant qualities, however they tend to take up a lot of space and so are restricted in places to grow. They are low-lying plants, which make efficient use of the sunlight and so are present towards the bottom of the pingo where there is a lot of grass and taller species such as Jointed Rush. Whilst the taller plants grow straight up, using less space, the rosettes are free to grown horizontally, as they have less competition for land from other herbaceous plants, which also grow close to the ground and need space. The presence of rosette species higher up the pingo lowers the SDI because of the amount of space they take up.
Evaluation
Although the investigation showed clear trends and mostly supported the hypotheses, the techniques used could have been improved to reduce errors occurring and increasing the accuracy of the data collected. Possible reasons for inaccuracy are summarised below.
Light meters were used to measure the light intensity, the light meters were held perpendicular to the ground, near ground level. However it is possible that the light meter was shaded when taking the measurement this would have lead to a lower light intensity than existed.
The soil samples were taken using a trowel and placed in a plastic bag. They were not experimented on until the end of the day, back in the lab. By this time water from the soil could have evaporated which would have reduced the moisture content of the soil and so caused inaccuracy in the data obtained as the soil may have, in reality, had more water. The soil samples were also only placed in the oven once. Usually the soil sample would be reheated so tat any remaining moisture in the soil (after the first desiccation) would be evaporated and an accurate value of percentage water in the soil would be obtained. The fact that the samples were not reheated means that water could still be present in the soil sample and this would render the data inaccurate.
Although the species key was a useful way in identifying the different species, in reality the plants on the pingo were all at different stages in their life span and so identification was harder than at first anticipated. This in turn could have lead to two plants being recorded as two different species when in fact they were the same. This would have increased the species diversity of the zones.
Grazing and trampling also had an adverse effect on identification. Some plants were unrecognisable and so were either recorded wrong or were not recorded at all. This in turn would have reduced the species diversity of the area. Grazing also affects vegetation growth because the species may have been eaten and not had time to recover, thus again reducing the species diversity of an area and yielding inaccurate results.
The data was obtained in a natural environment, for which there are no ‘exact’ results. The results obtained are influenced by a variety of factors for example, weather is uncontrollable, the long dry summer would have effected the amount of water in the soil especially since the pingo studied was south-facing and so would have had most sun exposure etc.
The pH was expected to be alkaline and between 7.4 and 8.5 and so was not expected to fluctuate greatly. The method used to measure the pH was not accurate enough in determining the exact pH as Universal indicator was used which is subjective to a certain extent and cannot be used to show exact values. Therefore it had to be concluded that the pH did not vary however it may have done but the technique did not allow for precise examination. The effect of this abiotic factor could not therefore be fully assessed.
Anomalous results
The line graph showing the distribution of water along the pingo has one anomaly. It is circled on the graph and is at zone 3 which had an intensity of 2.60 lux. This was an increase from zone 2 which had 2.40 lux. It was an unexpected result and appeared to be higher than it ought to be, this could be because of inaccuracy in measuring, however an average was taken which would have minimised the effect of any errors. It could also be due to the fact that zone 3 was lower on the slope and so would have got more sunlight as the sun was rising, before reaching its zenith and then throughout the day as well. Because readings were taken from 10.15 to 12.15 the sun would not have reached its zenith until midday and so the middle zones would have received more light, as the sun would not be high enough in the sky for the light intensity to be much higher in the upper zones.
In examining the line graph for soil water content, zone 4 seems to be an anomaly with a relatively high percentage of water in the soil. However this could be because the following zones, 5-7, had low moisture contents which in turn made zone 4 appear to have a high water content. The low water content in zones 5-7 could be because there were trees growing in between these zones. This would have resulted in the trees taking up most of the moisture, leaving the soil deficient of water. Zone 5 was on the middle of the slope and so exposed to wind, causing evaporation and transpiration. In effect the anomalies were therefore zones 5-7, for if there had not been trees there it can be assumed that there would be more water in the soil in these zones which would have created a more smooth graph.
The scatter graph correlating light intensity and SDI showed a negative relationship. Thus it showed that the lower light intensities yielded greater light intensities, this was not expected and opposed the hypothesis. The fact that many factors are involved in an ecosystem determining the carrying capacity of each zone and thus the species diversity could be used to explain this finding. For example the lower zones were more sheltered from the wind, this together with the low light intensity would have resulted in a lower rate of transpiration. The conditions would therefore be more favourable for species in the lower parts of the pingo than higher up, where water is scarce and light intensity high. There is one anomaly shown on this graph, that is, zone 4, at this zone there was a relatively high light intensity (2.3 lux) and SDI (16.93). In looking at the line graph for water content zone 4 also had relatively high water content (24.50%). The two abiotic factors (light and water) were therefore in abundance at this site and so naturally a high SDI would be expected.
Again the fact that many factors are involved in a wild environment could be used to explain why there was no correlation between SDI and water content of the soil, shown by the scatter graph and by the spearman’s rank statistical test conducted on the data which gave a value of 0.552 which was insignificant and o the null hypothesis was accepted. If water content was the only factor affecting growth, there would have been a relationship, however because more than one factor is involved (many of which were unmeasured) water itself can not be said to be the only factor affecting SDI, but it is when in combination with other factors. This is evident from the result of the chi-squared statistical test, which yielded a value of 36.556 thus showing that there was a significant distribution of water along the pingo.
Reliability
The fact that so many repeats were done means that the investigation was fairly reliable. The results obtained were all reasonable and no extreme anomalies were found. There was a reasonable justification for any anomalies that did occur.
The SDI figures show that species diversity increased with distance along the pingo. In looking at consecutive sites the SDI does not fluctuate greatly but steadily increases for example the SDI for zone 0 is 10.76 and for zone 1 is 12.04. This illustrates that there was a steady rise in the species diversity, which was expected, due to the gradual process of succession. This implies that the results for SDI were reliable. The only major fluctuation was between zone 3 (SDI=13.68) and zone 4 (SDI=16.93) which could suggest there was an error there. However as expressed earlier zone 4 had a reasonably high water content and light intensity thus making it a favourable site for growth.
The data collected for the abiotic factor of light was again fairly reliable. The fact that 5 repeats were taken at 1-hour intervals for three hours minimised the effect of extreme values, but also gave a fair representation of the light the zones would receive throughout the day. The light stopped being recorded after 12.15 because the sky became overcast with rain clouds and so if readings were taken they would have affected the average rendering them unrepresentative.
The data collected for water content again could be deemed to be fairly reliable as there were no major anomalies. However the samples were only placed in the oven once and so the results could be said to be inaccurate and therefore unreliable. The data collected for pH was not very reliable as it showed no variation.
Improvements and extensions
The main improvements to the investigation would be a modification of the techniques used to obtain the data.
A digital pH monitor could be used to accurately record the pH and see differences in the zones. This would improve the accuracy of the results and show the variation in pH along the pingo. The pH would affect enzyme activity and thus the rate of photosynthesis and growth rate.
The soil depth could have been measured quantitatively and a measurement for the depth obtained. This would have been more accurate than the soil profiles. The soil depth could have been measured at all of the sites not just 3 (zone 0, 5, 9); this is because the soil is not even throughout the pingo. The relationship between the soil depth and water content etc. could have been seen for all of the zones instead of assuming a general pattern of there being thick soil at the top of the pingo which thinned out over the slope and thickened again at the bottom of the pingo.
A soil moisture sensor could be used to measure the soil moisture content on the soil in the different zones. This would have been more accurate because the moisture level could be measured on the spot and sol samples needn’t have been taken. Repeats could also have been effectively done with the meter and it is a more time-efficient way of measuring the water content of the soil.
Taking the original sample number decided on (12) in the preliminary investigation would have improved the accuracy of the results. This was the optimum sample number, whereas using a sample number of 7 may have reduced the SDI value.
An extension of the investigation could be to examine the roles of the other abiotic factors affecting the vegetation growth. These include factors such as nitrate levels of the soil, humidity (measured using a hygrometer), oxygen level, and compaction and the level of wind. Instead of looking at a profile of the pingo the effect of aspect on the vegetation growth could also be investigated.
The investigation could look at the vegetation growth and species diversity of the pingo throughout the year, for the species diversity is likely to vary in the different seasons.
On the whole the investigation, although not completely accurate, obtained fairly good results. Trends in the species diversity were easily identified and the data for abiotic factors supported and justified the SDI values. Although not all of the hypotheses were proved correct, this could be attributed to the fact that the experiment was conducted in a natural environment not in the lab and so there are no ‘right’ results, instead a variety of factors combined account for the species diversity of an area.
Bibliography
Waugh, An Integrated Approach
Cambridge, Biology 1
Cambridge, Biology 2
W D Phillips, T J Chilton, A-level Biology
Fitter, Fitter and Blamey, Collins Pocket Guide of Wild Flowers
Biological sciences, Green Stollet and Taylor
Table titles for stats
Mention prediction of specific species in the conclusion. I.e. it supported hypothesis or not change structure so it is kite diagra-stats-support hypoth?
Mention statistical values in conclusion
Sort bibliography
Anomalies
Biological sciences