Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common Essay Example

Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common Essay Example Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common Essay Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common Essay A vegetation analysis has been performed at four sites on Wimbledon Common SW19 London, to assess the suitability of quantitative methods for determining human impact on the succession climax. Systematic stratified sampling based on the method of Querouille (1949) has been used Based on 25 sample points per site. A test of Yodas law; C=W? -3/2 has been performed on tree stands, where ? = density of a stand, C= dry weight of matter and w is a constant, by using a correlation test. Log (combined diameters) as the dependent variable (y) and log (distance between pairs) as the independent (x) variable. Three out of four sites gave high values of r, indicating that Yodas law may operate on the sample sites. This is thought to reflect human management of the common over 200 years as well as the mechanism of self-thinning. Using the point quadrat method (Curtis 1949) estimates of density d were obtained as: d= 1 / l 2 where l = ? li / n , where n = sample no and l i the determined lengths from the sample points. This showed discrimination between open and closed sites. A frequency analysis was carried out on this data to find the relative dominance of species X as: Relative dominance of species x= sum of circumferences for that species/ sum of circumferences for all species. Following the procedures of Clark and Evans (1954) these density estimates were tested for normality or a random distribution using the statistic: C=(rn- E(rn))/ (?/?N,) rn and E(rn ) the mean and expectation of the lengths of up to three nearest neighbours. Further following the procedure of Thomson (1956) using a chi squared distribution a further test of randomness was performed on nth nearest neighbours. Basal cover at 36 quadrats was estimated using a tenths scale. Finally a trampling index is proposed that assesses human impact. This has shown discrimination between open and closed sites. However in terms of overall trampling damage little serious impact has been seen outside of the established paths. A conclusion is drawn that both Conservationists and ecologists will be able to use the density measurements and the techniques more generally when planning management schemes for the common as well as the vegetation data and trampling scale to readily assess the impact visitors are having on certain areas of the common. Introduction. Wimbledon Common situated in southwest London is an extensive area of open land subject to multiple recreational use. For example there is a golf course, horse riding designated paths, cycle paths and numerous footpaths, some designated some not. Conservators are appointed to resolve issues of conflict demand use and to take decisions regarding conservation. In the absence of human interference this area would reach climax vegetation. Exactly what this would be depends upon a number of factors. The vegetation could vary on a local scale depending on the closeness to standing water, drainage qualities of the soil as well as the climate overall. The deciduous oak/beech forest is typical of southern England. Diagram 1 shows the proposed stages in this climax that could be appropriate to this area. It is important to realise that the vegetation pattern is never a static phenomenon unchanging once established but a highly dynamic one. Individual trees for example inevitably die or fall; leaving an opportunity gap in the light space that has opened up for other species to establish. This implies a pattern of a mosaic of patches might be become established caused by catastrophes, storms epidemics and diseases and so on. Some species actually inhibit their own re-creation at least initially. Their young saplings do not succeed paving the way for others. Beech is a case in point, thus replacement will be of ash, oak, or birch, but later these trees let the beeches back in. We can conclude that patches of oak, ash or birch are an integral part of the beechwood community. A.S.Watt in a study of beech-woods and found that when they are 60-80 years old the field layer can support wood sorrel but after another 10-20 years these are succeeded by brambles. The field layer may be very sparse with some species of tree for example Beech, dogs mercury, wood sorrell, wood barley grass and wood sanicle have been recorded as common, however if yews are present then not even these plants can gain a foothold. Oak (Quercus robor) has associated on the filed layer dogs mercury, wood sanicle and bluebells. As some areas on Wimbledon Common are left by the conservators to reach their natural climax whereas others are heavily trampled by humans, the opportunity exists to evaluate methods that quantify and qualify the scale of human interference. In this study a dual focus will be attempted. Firstly a look at the trees in their stands1 from the viewpoint of density2, and secondly to look at the ground cover3and assess both qualitatively and quantitatively human impact. Theory. A logical starting point is Yodas self-thinning law. (1963). In this study applied to trees. A derivation of this is given in the appendix. Yoda postulated that that the smallest individuals in a population are the first to die, leaving the larger individuals to gain weight. The law proposed was W= C ? -3/2 , or; in log form log W= log C- 1.5 log ? Where w = dry weight of surviving plants, ? = density of surviving plants C = a constant related to growth class of particular species being studied. The power 3/2 could vary between species as could the constant C. In some 80 species studies the range of C has been found to lie: 3.5 ;= C;= 4.3. A 3/2 power law implies that a change of three log units in mean plant weight corresponds to a change of only 2 log units in mean plant density. Although plants in a dense population become larger with age and as the population decreases due to mortality the law implies that the total plant weight will increase because mean plant weight is increasing faster than density is falling. This phenomenon is known as self-thinning. Incidentally there is enormous biological significance in this. For Farmers three are density limits in which young seedlings of a given species can survive. There are also implications in the filed of conservation of rare species where safe sites need to be found, for the planting of the seeds. One of the Hypotheses under test is that there is a positive direct relationship between the size of each pair of nearest neighbours and their distance apart. In particular self-thinning as opposed to mans imposition of pattern would be expected to comply with Yodas -3/2-power law. Larger individuals benefit from the death of smaller ones. Where regeneration takes place in a woodland gap a large number of seedlings immediately take advantage of the extra light but self-thinning operates during their growth to provide only one mature tree to fill the gap. The successful tree then suppresses new seedling growth. For the analysis of tree stands the method of plotless sampling has been chosen. This method is considered appropriate to forests where there are practical difficulties in delimiting the relatively large quadrats necessary for sampling trees. From the varied procedures mentioned in the literature given for completeness in appendix 2. Three have been chosen and suitably modified to suit the present project. By recording a minimum set of data it is possible to use any of the three methods. 1. Intraspecific and Interspecific crowding. Involves plotting the relationship between the log o combined diameters of each tree and that of its nearest neighbour against the log of the distance between them. This can be done for (i) all pairs of the same species (ii) all pairs of mixed species (iii) Combined data. A correlation coefficient is calculated where x represents the log of combined diameter and y the log of the distance of the nearest neighbours. Point Centred Quadrat method. A Point is established at random in the study area. Four quadrats around the point are marked. The distances from the point to the nearest tree in each quadrant are measured. Simultaneously through symbols such as triangles and squares the species type could be noted. p p could represent silver birch could represent oak could represent beech. p p The density of all trees in the study area is readily estimated as he average of all n length measurements. l = ? li /n. The overall tree density D= 1/ l 2 The frequency of each tree species encountered is obtained as a proportion of the total number of distance measurements made. fj = n j /n j= 1,2s, s is the total number of species, n j is the number of recorded distances to species j. From this the Density of species j: D j =f j D Adding to the data- sheet a record of the circumference of the tree at breast height (approx. 1.5m) we can use the following definitions in the project: Relative Dominance of Species X = Sum of circumferences for all species X /(sum of circumferences for all species) * 100 Relative frequency of species X = frequency of species X */ 100 (Sum of frequency values of all species) Relative density of species X = density of species X/(total density of all species) *100 Nearest neighbour methods. Morsita (1957) has suggested a type 3 estimator ( involving third nearest neighbours and above) applicable to certain type of non-random distribution. This might prove useful in our situation where Wimbledon Common is managed to a great extent in terms of tree density and so on. The distance r to the nth nearest neighbour n;= 3 in each of k sectors at N points is measured. In view of the greater number of sampling points required, a simpler scheme needs to be found here. D1 = 1/pi (n-1)/N ( 1/r) The distance from one tree to its three nearest neighbours will be obtained, and following a procedure of Clark and Evans (1954) test will be conducted on the randomness or otherwise of the distribution of distances. The estimate for density m0 will come from the point quadrat method. Choice of Sampling Procedure and Quadrats. Cochran in 1963 pointed out that There must inevitably be an element of subjectivity in sampling procedure because the boundary within which a set of samples is taken are fixed by the ecologist on the basis of his judgement of what can be suitably described as one unit for the purpose in hand. Parts of an area can be sample separately if there is doubt as to its homogeneity. A choice has to be made between random and systematic sampling. In random sampling an estimate of the mean is available plus the standard error of the mean i.e. the precision of the mean. The use of t tests to compare two sites is available. In systematic sampling there is no indication of precision and no possibility of assessing the significance of its difference from the mean in another area. However systematic sampling is preferred by many workers on the grounds that it is more representative of variations over the area and hence likely to give a better estimate than random samples and that it is easier to carry out I the filed. Bordeau (153) in his study on density and basal area of forest trees found any gain in accuracy from systematic sampling to be slight. In random sampling any point within the area has an equal chance of being represented in the sample. Stratified random sampling divides the area into blocks taking the same number of samples from each block using random co-ordinates. Quenouille (1949) suggested a method of systematic unaligned sampling. The area is dived into blocks as shown in the diagram 2 below. Keep the x co-ordinate fixed and randomly choose y in a row. Repeat for the other rows with different xs. Smartt et al (1974) found the accuracy increases in the order random, systematic stratified random and stratified unaligned systematic sampling. Whatever method is chosen one important criterion must be borne in mind. An appropriate scale must be chosen for the co-ordinate axes. If too coarse a scale is used so that only a limited number of possible positions are available the system degenerates into a random sub-set of points on a very limited grid. This implies the same disadvantage of possible bias in any one set of samples as systematic sampling. On the hand the smaller the quadrat the greater the chance of significant edge effects due to the observer consistently including individuals that ought to be excluded or vice versa. Extremely false conclusions can also be drawn see illustrations below.(diagram 3) On the basis of the above discussion the following decisions have been made: 1. To select for ground vegetation cover the method of quenoiulle (stratified systematic unaligned sampling.). Sophisticated t analysis will not be used on the ground cover data. 2. A quadrat size of 30mx 30m will be used, divisible into 9, 10m x 10m blocks. 3. For tree analysis plotless sampling methods will be chosen avoiding consideration of quadrat design. Choice of Cover measurement. Two schools of thought have emerged on describing and recording vegetation cover that of Domin and that of Braun Blanquet. For convenience a table is shown in the appendix of these scale. However it was thought better for this project to use a system of recording a quadrat base on tenths coverage of the basal layer. As the site area will be 30m x 30m a splitting into 9 blocks each of side 10m seems reasonable. Vegetation will be estimated on a scale of ten. Detailed Plan and Methods. Apparatus. Measuring tape, Light Meter, stakes or markers, chalk, clipboard, prepared data sheets, pencils, map. Preliminary work. 1. Conduct preliminary site survey, to get a feel for the area and to see what can be usefully accomplished. 2. Talk to Range Warden, obtain useful information on human management of the common, and also vitally and respectfully inform him of the intended research and aims and as to where the research will be carried out. 3. Prepare data field sheets for four sites (samples are shown below). For plotless sampling 8 columns are required of length in four quadrants together with associated tree diameters including a key for species identification. For nearest neighbour analysis 9 columns are required for tree no, distances to three nearest neighbours and associated tree diameters. 4. Obtain table of random numbers. Select 3 blocks of 4 single digit numbers (see diagram 3) 5. Obtain an assistant for the recording of data and help in setting stakes, marking trees and in holding the tape. 6. In the field: Select site. Chosen quadrat size is 30m x 30m. This can be paced out and staked in 10m intervals in both x and y dimensions. Adhering to the pre-ordained random numbers in y and fixed numbers in x for each row ,according to systematic sampling method chosen, the ground cover of the vegetation is estimated in tenths. Any notes made on the sheet according to the Braun-Blanquet school of notation. Any new species not recorded on the sheets should be added. The trampling scale score, canopy cover and light readings can be incorporated on the sheet. 7. Select 4 sites in all, under two criteria. Two should be largely unmanaged; two should be largely managed. The word largely implies inherent uncertainty given the relative un-isolation of the common. Show these on the map. 8. For the plotless sampling data start at a sensible point in the site area. In this context sensible refers to a number of criteria. Single plantations can be useful. Mixed plantations can be useful. Note that the site has already been chosen under a range of criteria. Move around the site taking representative readings until 25 sets of trees have been obtained. 9. Under the point quadrat method select the sample point. Mark it clearly. (Put the assistant on it!) Measurement of the distance in paces will be good enough or with the measuring tape (making sure of consistency in method of recording). Record the circumference of that tree at breast height. Try to be consistent in this in view of any vegetation causing difficulty in approach, or awkward geometry of trees. Note the species of each tree using a key system for ease of recording, (see data sheets). 10. For the nearest neighbour method. Choose a starting tree. Measure its circumference. Then measure distance to its nearest neighbour and measure its circumference. Repeat for the three nearest neighbours in total. No need here to record the species. Except in the general notes comment may be made as to the nature of the area. In particular note that the measurement of a particular tree does not preclude that tree from being anothers nearest neighbour. 11. Record all data by the researcher (me) verbally calling out the measurements and the assistant recording them. It is often sensible to have him verify what he has written down to minimise errors of recording. 11. At all times observe a safe procedure but equally as importantly attempt to disrupt the ecosystem as little as possible. This is particularly important at the two sites that are left by the conservators as little managed as possible. Modifications to plan as carried out in the method. 12. A minor modification resulted in the field in that the measuring tape was in fact in imperial units. In the original data sheets circumferences are recorded in inches and some distance measurements. Other distance measurements were recorded in paces. My pace was measured in cms. (about 30cm) In translation to the spreadsheet appropriate conversions were undertaken , i.e. 1 inch =2.54 cm. Examples of data sheets used in the field. Field Data-Sheet: Plotless Sampling. Point Centred Quadrat Method. Sample point no l1 r1 l 2 r2 l 3 r3 l4 r4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Field Data Sheet: Nearest Neighbour Analysis. (Site Designator):- Tree no Circumference (cm) r n1 dn1 r n2 dn2 r n3 dn3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Field Data-Sheet : Base Cover. Site: Ground Cover % 1 2 3 4 5 6 7 8 9 Average Leaf Litter Branches/twigs Bare ground Short grass Long grass Soft rush Brambles Holly Tree saplings Ferns gorse Trampling Score The trampling scale index. 1. No impact on vegetation- flower heads present and stems of plant not broken. 2. 2. Vegetation affected-plants are mainly grasses, stems bent 3. 3 1%-25% of topsoil expose-plants very short or cushion form, some damage 4. 26%_50% of topsoil exposed-plants very short or cushion form clear damage. 5. 51%-75% of topsoil exposed-plants very short or cushion form, very clear damage. 6. 76%-100% of topsoil exposed-plants very short or cushion form, severe damage. Results and Discussion. The original results are presented as carried out in the field. These have been copied onto an excel spreadsheet for analysis and converted where appropriate into SI units. Various plots are presented below to illustrate some of the data that has been collected. Four sites were chosen two in relatively open ground, two in more dense plantations. A frequency count of each tree species is recorded below. Site1 Site 2 Site 3 Site 4 Silver Birch 95 Beech 8 Beech 56 Silver Birch 35 Oak 3 Oak 29 Oak 22 Oak 48 Other/holly 2 Silver Birch 60 Silver Birch 17 Beech 6 Beech 0 Other 3 Other 5 Other 7 This summary table provides useful information on the character of the sites. Sites 1 and 2 consist predominately of silver birches, whereas the oaks and beeches dominate sites 3 and 4. However in the denser stands there is still a significant number of silver birches and this may well affect the results. In Sites 3 and 4 however with the greater number of mature oaks and beeches this symbolises that these latter sites have been better able to reach a state of maturity or climax, than those of the former have. Correlation data for Yodas law are summarised in the table below for the four sites. Site no 1 2 3 4 Correlation Coeff. r 0.71 0.81 0.42 0.84 The data have brought one of the surprises of the study. I would have expected the Pearson correlation coefficients to be nearer unity in the mature forests and perhaps not so in the silver birch plantations, implying a direct association between tree spacing and tree diameter for pairs of trees sampled. It is to be noted that the coefficient is highest in the supposedly more mature woodland in site 4, than it is in sites 1 and 2, although these two sites have returned a high value. The small sample covering an extremely small fraction of the area of the common must be borne in mind when analysing all the data in the study. A significance test could have been performed on these correlation coefficients but this will be held over for a further study. Yodas self-thinning rule might well show some correlation because of the influence of tree management. As trees are cut down to make open space or to let other plant species flourish . In the third site a poor correlation has been observe d. Various hypotheses still need to be explored to explain the pattern of results. (i) The sampling was inadequate in terms of numbers sampled. (ii) The measurements were seriously incorrect. (iii) Yodas law does not apply as either man or some earlier catastrophe has thinned the trees below their natural self-thinning level . Yet a correlation appears for another reason. (iv) Yodas law does apply and the results bear this out largely. Whilst accepting that the number sample at each location was low, it is unlikely that gross errors were made in the measurements attention must focus on the third and fourth assumptions . The Common management have more than likely restricted the number of trees especially in areas 1 and 2 to allow a wider access for walkers and in so doing the density of the trees is below that which they could have attained, and yet a correlation between tree diameter and distance still exist but it might not be finding a 3/2 power law but some other relationship.. Indeed in conversation with the park ranger I learned that further thinning work was planned in conjunction with Kingston University at site 2. Conservationists face this dilemma of wanting more species to establish in areas where more light is allowed to penetrate the surface, as against the philosophical wish of other conservationists of leaving things as they are and for areas to develop naturally. In a crowded urban environment such as the conurbation of London it is probably inevitable that the former policy would win out and that areas have to be managed to cope with multiple demands on them. Density calculations. To further refine the notion that man management has affected the area, tree densities have been worked out according to the point quadrat method. A summary table below shows the computation that have been undertaken on the spreadsheet. The units for these densities should be considered as numbers of trees per square metre. Site Number 1 2 3 4 Point transect 0.23 0.12 0.04 0.05 Sites 3 and 4 have been found to have a lower density than sites 1 and 2. This calculation therefore tends to confirm a trend that was already being formulated that the more mature woodland with its older and higher trees has lower densities of individual that the younger silver birches of sites 1 and 2. Silver birches tend to have lower girths ( at least this study has fond that) than mature oaks or beeches and that more can be packed into a given area. Of course it is not just the basal area that determines the thinning density it is also a function of the overhangs and morphology of the higher branches. Interestingly this concept of morphology forms a detailed subject in itself. Plants and trees are different to animals in that they do not have a modular form. Shape can be extremely variable. White has conducted a study into subject principally on silver birches. My photographs of Oaks on Wimbledon common have revealed some very strange specimens indeed. The Ranger gave me an explanation in that he thought the poor drainage of London Clay responsible for their non-upward growth. Many of the oaks on the common had this deformation, whilst others appeared in normal stands. The results have demonstrated that discrimination between sites is possible with calculations of the type used. There are others mentioned in the literature, which could be similarly evaluated in the field in a subsequent study. The author admits to being surprised at the low densities being found. Photographic evidence of some areas would suggest a low value , whereas others would suggest for silver birches a much higher packing fraction. However it again boils down to the number of samples taken and where they are taken for a fuller picture to emerge. Gathering together the remaining calculations: The table below shows the computations for frequenct density and relative dominance. The useful property of the definition of relative dominance is that the weight given to larger trees such as the oaks and beeches more than compensates for their fewer number. It gives a more accurate impression than simple frequency density of the true impact that a tree species has in terms of basal area ,and hence light requirements and competition for resources and so on. One feature from the table is that silver birches are highly dominant in open ground, whilst maintain a fair degree of dominance also in closed ground. Oak only managed first place in one of the sites , Beech also in one. Of course the small sample again and the way the sampling was conducted mitigated against all oak or beech dominance. However this data does provide a pointer that a succession climax is not being reached on Wimbledon Common. Site 1 Site 2 Site 3 Site 4 Frequency Density Oak 0.68 3.42 0.78 2.28 Silver Birch 21.65 7.08 0.60 1.67 Beech 0.46 0.94 1.99 0.29 Other 0 0.35 0.17 0.33 Relative Dominance Oak 0.06 0.59 0.30 0.77 Silver Birch 0.93 0.26 0.06 0.12 Beech 0.01 0.13 0.62 0.06 Other 0 0.01 0.02 0.06 Thomson, Clark and Evans have attempted to go further and look for evidence of non- random distributions in tree stands. As the procedure they describe is applicable to the measurements I had already collected, with the proviso that my estimate of density will come solely from the point quadrat method and not from nearest neighbour analysis .The appendix 3 summarises data relevant to the calculation and shows two sample calculations. These authors assume that a measure of departure from randomness in a population of plants can be measured. The distributions of distances to neighbours in first order second order and so on are related to the chi-squared distribution. The advantage in using second and third nearest neighbours (Apart from the increase in accuracy of density determination in random populations) is that it should be possible to detect larger scale heterogeneity than by merely using the distance to the nearest neighbour. In the distribution (details not given here) the statistic N x where x n is the mean of the N observed values of x is distributed as chi squared with Nn degrees of freedom. Chi-square gives a simple test of randomness. A probability of Chi 0.95 indicates significant overdispersal of individuals, the distance being smaller than expected, while a probability 0.05 indicates significant underdispersion. From the calculations there is evidence of overdispersal from the nearest neighbour analysis ,because the probability values have turned out to be very low indeed. Ground Vegetation and Trampling Scale Analysis. Turning to the more subjective but nevertheless quantitative data on the ground layer. Averages for each category have been worked out and displayed in the form of a bar chart below. The limited number of samples taken over the limited number of sites obviously limits the description of the vegetation that can be given for the area. However a number of points emerged from the study. Bare non-open ground was founds at site 3 mature beech-oak woodland. The canopy layer in early spring as leaves began to emerge was estimated at 70%. It was thought that the field layer was largely a function of the microclimate of the canopy layer rather than the effect of huge numbers of persons trampling the area. Although a stream existed at the bottom of the glade and the golf course existed at the top on higher level ground, and undoubtedly humans such as myself visited the area. The overall scene of bareness indicated a natural explanantion. Where in any quadrat a footpath exists then inevitably consequences flow from that. In some locations not sampled but viewed generally, wide paths (One is seen on an annotated photograph) exist and at the season of the year ( Early spring) it appears that trampling exposes bare topsoil, as well as the more natural phenomenon of waterlogging. This would indicate severe damage on the trampling scale chosen. Other more minor paths appeared to be in good condition, in that they were overlain with grass albeit is short cushion form. Conservationists again face a dilemma here. Concern is expressed in some quarters that too many visitors destroy that which they have come to see. As evidenced in the phonograph busy paths can prevent any regeneration of plant life. On the other hand paths encourage visitors to keep within narrow restricted ranges and discourage them from straying further. This helps to conserve plant material away from the main paths. I observed on my study how difficult it w as to stray from sidepaths to take measurements in view of the dense underlayer often of bramble, holly and so on. The bar charts clearly bring out differences that do exist between the sites. For example the bramble appears most often in the darker more mature woods. Leaf litter and branches are very noteworthy features of the closed areas.. The small sample has just picked up some of this. Ivy appears to be a feature of some of the darker area. In the more open silver birch stands it was possible without too much difficulty to step between leaf litter, and occasional bramble to measure trees. The fact that more people might stray in this open area is the most likely factor other than man management that denser woodland does not form. One consequence I noticed in some areas where paths had formed, these allowed more light to penetrate the dense woodland canopy which may be beneficial, also the problem arose t of unwanted plant species at the borders of such paths, principally nettles. This voracious species appears to have spread along paths and slightly into interiors in some parts of the common. In the more open areas not always sampled by my quadrate there we extensive area of heather and gorse. Heather existed near site 1 in extensive carpet form. These species seem to relish the more open and well-drained areas of open parkland. Heather is a probably acceptable form of seating for picnickers in the summer months and the rangers choose to leave these areas for recreation at the expense of establishing silver birch saplings. The survey method is therefore capable of reproducing information to ecologists as the field layer tells them in effect the state of the woodland and its canopy layer. Any damage by too much human impact can be assessed using such methods. Conclusion and Evaluation. Necessarily given a short time span for an inidiuval study one cannot hope to solve completely the difficult problem of describing the distribution of flora in an area. The problem of density measurement has been tackled at albeit at a simple level. This problem which entails decision making on sampling and what to sample is the prerequisite for the next fundamental problem that of describing pattern, i.e. what distribution will describe the tree stands. For example. Does a Poisson distribution describe the vegetation? Other interesting possibilities for further research have been revealed by the study, that of the morphology and form of trees. This appears an equally difficult subject. On the more human side of things issues are raised by conservationists on how to manage an area such as Wimbledon Common, quantitative and other more subjective determinants of distribution of vegetation all have their place, when trying for example to estimate the impact of visitors and as to how this should if at all be minimised. .In future work I would want to study more on the methods of selecting the quadrates, and to study the effect on results on quadrat size, which I have briefly seen in the literature. I would want to look further at the methods available and their problems for looking at surface cover on plant vegetation. Sampling frames with pins and so on. Further I would want to correlate my measurements with those of elsewhere on other woodlands and sites and to see how they compare with literature values in other places. This leads on to questions of the physical factors such as soils drainage and microclimate generated by the plants themselves, the factors that determine the distribution as we see it today. In other words the field for study is huge, this individual study has merle scratched the surface. The simple point quadrat method is capable of discriminating between sites in it measurement of density. The nearest neighbour methods can assist in determining if a law similar in form to Yodas law applies as well as to assisting in the statistical analysis on the randomness or otherwise of the distribution of trees in a stand.