Saturday, 7 June 2014

How does the resource availability hypothesis hold up with common garden snails (Helix aspersa) feeding on winter wheat (Triticum aestivum)?

How does the resource availability hypothesis hold up with common garden snails (Helix aspersa) feeding on winter wheat (Triticum aestivum)?


        Chris Gibson


Project supervisor: Dr. David Pilbeam



This study will test whether the resource availability hypothesis is upheld in feeding trials between winter wheat (Triticum aestivum) and common snails (Helix aspersa). The hypothesis predicts a positive trend between growth rate and grazing. In feeding trials at the University Experimental Gardens this was proved to be upheld with an increase in final weight of the high nutrient treatment plants supporting previous studies. The increase in mass is believed to be a result of increased tillering or shoot growth stimulated by grazing. Snail dispersal based on previous nutrition regimes was also tested. It was found that prior nutrition strongly influences snail dispersal time. Tests on snail pot choice (‘high’ or ‘low’ nutrient treatment plants) were however inconclusive. It is believed that this is a result of the ‘low’ nutrient treatment not being low enough to cause a significant difference in plant growth.  



What is the Resource Availability Hypothesis?

The resource availability hypothesis of antiherbivore defense was originally devised in order to explain the variation in the levels of herbivory of plant species in diverse ecosystems. It was based upon an original hypothesis that mature leaves of slow growing species adapted to resource limited environments were less preferred as a food source than mature leaves of rapid growing species adapted to more productive and resources rich habitats. The first time it was tested was in a study of nine woody South African plant species and kudu (Tragelaphus strepsiceros) and impala (Aepyceros melampus) preferences for those species (Bryant et al. 1989). The preferences for the plants were previously known what wasn’t known was the inherent growth rate of the plants, plants which were either palatable or unpalatable species. The growth rates of the nine plants common in the study sites was determined from glass house experiments. The comparison of predicted growth rates based upon kudu and impala preferences with the actual growth rates obtained was use to uphold or disprove the hypothesis. A positive correlation between predicted and measured upheld the resource availability of antihervibore defense whereas negative or lack of a correlation disproved the hypothesis. All results with the exception of Grewia flavescens (which grew faster than other related species, however is probably adapted to fertile soil) fit the hypothesis, which could be used to explain why large African herbivores feed less on woody vegetation in the unpalatable woodland and more on the palatable woodland.
This was backed by other studies, which showed that large African herbivores feed less on vegetation that is found on infertile soil than fertile soil vegetation. It is suggested that the relationship between soil fertility, vegetation and large herbivore foraging is due to infertile soil plants being poor food as it has a low ratio of nutrients to fibre and chemical defenses (Bell, 1982).

Elberse et al. (2003) conducted a series of experiments on nine wild barley (Hordeum spontaneum) populations and their susceptibility to greenbug (Schizaphis graminum). The study was set up to test the relationship between potential relative growth rate and the barley’s susceptibility to the bug under two different nutrient conditions and in light of the resource availability hypothesis (RAH). The RAH predicted a positive correlation between potential relative growth rate and susceptibility (in line with Bryant et al.’s work), results however showed no correlation with high nutrient plants having on average 22.8 nymphs per plant and low nutrient plants 24.3. As the RAH expects there to be some trade off of growth rate for plant defense and as this was not present the RAH hypothesis was, in this instance, discounted as effecting the relationship between wild barley and greenbug. However previous studies have shown both a positive (Gruber and Dixon 1988) and negative effect (Salas et al. 1990) of nutrient levels on aphid performance if not specifically plant susceptibility.

The difference between the Bryant et al.  and Elberse et al. examples are that aphids and impalas feed differently on plant matter. Aphids feed on the sap of a plant, which has an effect on the plant as a whole, whereas animals and insects that graze only affect leaves or stems. This can be shown with another example involving Triphabda beetles feeding on goldenrods (Solidago spp.)(Brown 1994). In this study the resource availability hypothesis was upheld as grazing increased relative growth rate and as a direct consequence increased above ground biomass.   

Diverse usage

As a scientific hypothesis resource availability has a diverse usage in scientific literature. Papers have been published treating resource availability like an economic model (Neumayer 2000) or using an economic analogy in order to explain trends seen in experiments (Bloom et al. 1985). The flexibility of the hypothesis has allowed it to be widely used in research studies. One piece of work involved manipulating resource levels and its effect on the Argentine ant (Linepithema humile). In this study the effect of altering levels of protein in different colonies diets and its impact on pupae was investigated (Aron et al. 2001). The ants were provided with high, intermediate or no extra protein in their diets, it was shown that protein increases the number of sexual pupae produced. The increase in protein meant females were more likely to be queens than workers and the total proportion of males within the population was higher. The un-supplemented nests showed that protein availability influenced the proportion of a brood that is culled. The culling showed a direct relationship to protein availability, the lower the level of protein the more sexual pupae culled.

Andersson et al. (2005) looked at differing resource levels (mircoinvertebrate and zooplankton quantity) on Arctic char (Salvelinus aplinus). A series of pond and lake based experiments were carried out with results showing that differences in the resource levels caused both morphological and behavioural changes in the char. The fish that were in the complex environment (high levels of both resources) had a higher dependency upon the zooplankton than their simple environment counterparts. The complex environment fish were subsequently morphologically dissimilar to the simple environment fish as a direct response to this preference.

Byers (2000) showed that an increased level of resource availability decreased the dispersal rate for larger (adult) esturine snails. Further experiments showed that smaller snails had a higher dispersal rate regardless of the resource levels present. This supported other studies, which had shown less competition amongst the young smaller snails. One possible hypothesis for these results was suggested as being some form of genetic behaviour present when the snails are young. The behaviour is thought to cause younger snails to disperse more readily in order to avoid competition.


Nutrient availability and its effects

A review article by Aerts and Chapin III (2000) spoke about the effect of increasing a plant’s need for nutrients and this impacting upon the plants capacity to absorb the nutrient and how this capacity is specific for that nutrient which most limits a plants growth. For example if a plant requires more N then the need to uptake N will decrease the ability to absorb other nutrients that do not limit the plants growth. At conditions of low nutrient supply the plants ability for uptake will be at its maximum. It will also reduce nutrient leakage at the roots thus allowing it to acquire nutrients at lower external concentrations (Kronzucker et al. 1997).

Trials ran by Wilson and Tilman (1991) in a 30-year-old field. The experiments concentrated on the effects of fertilization and disturbance on the plant communities. The experiments were conducted on 104 5x5m plots separated by a 2m corridor of untreated vegetation. Tilman had already demonstrated that nitrogen had the greatest limitation on plant growth within that community in which dominant species included Schizachyrium scoparium, Rumex acetosella, Lespedeza capitata, Solidago nemoralis, mosses and lichens. As it was the greatest limiting factor N was chosen to represent fertilization within the experiments. There were four treatments: no added nitrogen and highest rate of disturbance, no nitrogen and no disturbance, highest added nitrogen and no disturbance and finally highest rate of nitrogen and disturbance. It was shown that increasing the levels of nitrogen increased the total community biomass. The species richness within the plots also increased with nitrogen supply, this time however only in undisturbed plots. In both the undisturbed and disturbed plots vegetation height increased as light penetration decreased. This was coupled with a decrease in root: shoot ratios with the added nitrogen. Leaf allocation decreased with disturbance whereas flowering allocation actually increased despite stem allocation being unaffected by disturbance levels. Similar results were found in yellow nutsedge (Shibuya et al. 2004) where increasing nutrient supply led to increasing plant productivity and associated traits of this, i.e. flowering allocation. Plant productivity could also be seen as being a form of competition between plants, where increased reproductive success is the outcome of successfully out competing neighbouring plants. This has been backed up by competition field studies where manipulation of resources was shown to affect competition intensity (Davis and Pelsor 2001).

A different set of experiments by Wilson and Tilman (1993) this time on a native perennial grass Schazchyrium scoparium only and using a similar method to their previous experiment with disturbance equaling annual tilling which removed all vegetation in each of the 5x5m plots. There were two treatments of N simply non-added of 17gm-2yr-1. They were able to show that above ground competition was greatest in plots with the lowest light penetration. Lower nitrogen availability increased belowground competition and decreased significantly with increasing nitrogen availability.

Grazing, plant defence and resource availability

Grazing by herbivores reduces plant fitness. Increasing any form of plant defence either inducible of constitutively expressed is therefore expected to be selected for. Induced responses to herbivory are likened to immune responses in that they can reduce the performance or preference of herbivores. Adaptations made by the plants are assumed to be beneficial to them. There is however a lack of experimental evidence demonstrating benefits. There is evidence showing that following grazing plants increase their levels of chemical, physical and biotic defences in many species. Some work has been attempted to prove that these defences increase fitness by reducing herbivory (Agrawal 1998) using wild radishes and testing 3 conditions; induced plants, leaf damage controls and overall controls. Early season flower number was measured as a correlation of male fitness. The induced experiment was conducted early in the year and then the plants were left to be grazed by natural herbivores. The induced plants showed a greater resistance too herbivory than the control and leaf damage control plants with female reproductive fitness of the plants being recorded as being 60% higher. This protection was not species specific, with all small grazing herbivores and aphids affected.  This is an example of defence plasticity; plastic defences are when a single genotype can produce different phenotypes depending upon the environment. Plastic responses are favoured by selection if plants can respond appropriately to reliable information in their environments. The other side of this is that if a plant is to act of inaccurate in formation it would actually lower plant fitness as additional resources are being diverted to less essential areas of the plant (Karban et al. 1999).

Transgenerational effect is another defence strategy. This is also known as maternally induced defence. In this non-lethally grazed plants produce defences against herbivores but will also produce offspring that are better defended when compared with plants produced by non-threatened parents. This is a form of phenotypic plasticity which works across generations as well as within individuals within the original generation. Endowing offspring with defences against future grazing which the parent plant has already dealt with will increase the lifetime reproductive success of the second generation. This occurs due to altering of the offspring’s phenotype. Work has been done on wild radishes (Raphanus raphanistrum) taking them and exposing them to damage by a specialist caterpillar (Pieris rapae) induced a ten fold increase in indole glucosinolates (mustard oil glycosides) as well as a 30% increase in density of setose trichomes on newly formed leaves of the damaged plants when compared with control’s (Agrawal et al. 1999). In these tests there were control plants and plants that had 50% of each leaf consumed by a caged caterpillar. In the experiments where the caterpillar grazing occurred hydroxylated glucosinolates increased in concentration whereas other classes of glucosinolates decreased. The caterpillars feeding on damaged plant seedlings gained 20% less weight than those which were fed on the seedlings of undamaged plants. This discrepancy was not explained by seed mass variation of investment in primary metabolites. Seeds from these plants did not differ in nitrogen of carbon content when compared with seeds from undamaged plants as so investment in seedling defences was concluded to be the reason.

Another defence strategy which links in with this is the optimal defence theory. This expects there to be a negative relationship between growth and defence and so is similar to the RAH. This has been demonstrated in tomato plants (Wilkens et al. 1996). In these tests the effect of resource availability on intraspecific and within-plant allocation of soluble phenolics (rutin and chlorogenic acid) was investigated. By measuring mass as well as physical and cellular attributes of the plants the effects of resource availability on growth was also measured. The experiments showed that plants grown in low resources contained low levels of soluble phenolics and low plant mass. Plants grown in the intermediate solution showed high phenolics but had inhibited growth. Those plants grown at high levels of nutrients however had high growth but not higher phenolic concentrations. The differences in phenolic concentrations were large enough to have potential consequences for the insect herbivores feeding on the tomato plants. This would have a knock-on effect of increasing the grazing on the tomato plants grown with lower nutrient supply. Display of this is expected to depend on the species of plant being tested, i.e. not every plant will display chemical defences like this some may simply decrease their attractiveness to herbivores (woody stems etc) as a means of defence.

Leaf lifetime can also be determined by resource availability as it affects the relative advantages of defences with different turnover rates (Coley et al. 1985). In fact the growth of leaves has been shown to be strongly linked to bother resource availability and plant defence strategies. Kurokawa et al. (2004) used dark house experiments to show that a species which traditionally grows in the shade (Eusideroxylon zwageri) has slow growth and in order to prolong lifespan devotes 35% of all production to defensive substances (condensed tannins and lignin’s). This is inline with what the resource availability hypothesis would predict for a slow growing plant. This strategy is advantageous for survival in dark conditions as these lignin’s and tannins help to prolong the lifespan of its leaves and stems (tannins leaves and lignin’s stems). The growth differentiation balance is another theory, which is different to resource availability and is used in explaining the secondary metabolism and structural reinforcement that are physiologically constrained in dividing and enlarging cells. This diverts resources away from production of new leaf area (Herms and Mattson 1992).

 The aims of the current study

This study will test whether the RAH is upheld in feeding trials between winter wheat (Triticum aestivum) and common snails (Helix aspersa). In order to test this wheat will be grown in two nutrient treatments a ‘high’ nutrient treatment and a ‘low’ nutrient treatment. RAH predicts that as the plants in the ‘high’ solution will have a greater RGR and as wheat is a rapid growing species they will be more highly grazed upon than the plants grown in the ‘low’ nutrient solution. Another aim will be to look at snail dispersal and choice. If as previously stated an increase in resource level increases snail dispersal rate then would treating the snails to different diets prior to the trials affect this? For example starving the snails for 24hours prior to trial is predicted to decrease dispersal rate (or time till first movement) when compared to them being fed on wheat or fresh vegetation. The difference between the fresh and wheat prior feeding treatment however is uncertain. Also uncertain is the snail’s final choice (‘high’ or ‘low’) during the preference trials. While grazing on the high nutrient plants is expected to be higher than on the low nutrient plants it is unknown as to whether prior feeding will affect the preference trial results. This will also be tested. 



Materials and Methods

Snails and Wheat

Fourteen common garden snails of various sizes were collected from the School of Biology Experimental Gardens. These snails were kept in a tank that was aerated but had air holes too small for the snails to escape through. They were regularly fed and misted in order to ensure their survival during the course of this investigation.

Two crops of winter wheat were sown during the course of the experiment. The first batch was sown on 23/09/05 and was used in the first free preference trials. The second batch of wheat, sown on 8/11/05, was used for the final four preference trials as well as the feeding experiment. The wheat was all grown under glasshouse conditions and fed either a ‘high’ nutrient solution of a ‘low’ nutrient solution depending upon which treatment was being applied to it. The high nutrient solution was made up of; KH2PO4 - 0.25mM, K2SO4 – 0.5mM, MgSO4 – 0.5mM, Ca(NO3)2 – 1.0mM, IronEDTA – 0.04mM and micronutrients (H3BO3 – 0.0153mM, MnCl2 – 0.0005mM, ZnCl2 – 0.0005mM, CuCl2 – 0.0005mM, Na2MoO4 – 0.0024mM). The low nutrient solution was made from; ; KH2PO4 - 0.0625mM, K2SO4 – 0.125mM, MgSO4 – 0.125mM, Ca(NO3)2 – 0.25mM, IronEDTA – 0.01mM and micronutrients (H3BO3 – 0.003825mM, MnCl2 – 0.00125mM, ZnCl2 – 0.000125mM, CuCl2 – 0.000125mM, Na2MoO4 – 0.0006mM). The wheat was grown in sand in 95mm diameter and 90mm tall pots and fed from the bottom up by supplying nutrient solution in a saucer 130mm diameter and 25mm deep. To allow for individual growth each saucer was filled up to the top and constantly topped up.

Preference trials

The preference trials tested the null hypothesis of the predictions mentioned earlier. The wheat was placed in a preference board (figures 1 and 2). This board allowed the snails to move to any of the plants in the test area. Testing occurred on individual snails and each trial lasted for twenty minutes. This was determined after a mock trial was run using 10 snails at a time (results not shown). The snails interacted with each other and as such their movement was not felt to be a reflection of their own choice. The twenty-minute time limit was decided as after twenty minutes the snails had either chosen a pot of had stopped moving altogether. For each trial the movement of the snail was recorded. The snail’s response was logged as either staying in the middle of the board (or moving back to it), movement to a high nutrient plant or movement to a low nutrient treatment plant. The snails themselves were either fed wheat, fresh vegetation (randomly selected from the gardens) or starved for 24hours prior to the trial commencing. For each treatment 10 separate snails were recorded as repeats. All snails were placed in the middle of the trial board and their original positioning was random. To keep the snails on the board a ring of salt on top of Vaseline was applied to the outside edge.

Figure 1, dimensions of the trial board in mm.

Figure 2, the set up of the trial board. The ring of salt around the outside kept the snails within the trial area, the saucers under the pots were the means by which the plants could be watered and the plants themselves were accessible to the snails during the entire course of the experiment.

Feeding trial

The feeding trial ran for four days and three nights. All fourteen snails were involved and their positions were logged daily. The snails were not touched during the trial and were left on the board. This was designed to test the null hypothesis based on the predictions. As well as the salt ring a second salt ring was set up on the bench to prevent any snails escaping. As well as the trial board the where the snails were allowed to graze a replicate trial board on which no snails were placed was set p to allow comparisons with control plants that were grown in a board but were not grazed. Comparisons were based on above ground dry weight of individual plants.

Statistical analysis

Normally distributed data was analyzed using ANOVA and T-tests. Non-parametric data was analyzed using a Kruskal-Wallis test.



 Firstly a series of experiments were conducted to explore whether or not the snails would eat winter wheat. An observation experiment and a prolonged feeding experiment were set up. In the feeding experiment the snails were left for five days with only wheat shoots for food. The difference between the original mass of wheat and the final mass was 41.06g. This was compared with a similar mass of wheat left un-grazed for the same period of time to determine mass difference due to water loss and plant growth. The wheat from the drying experiment differed by 11.58g from its original mass. The extra difference in mass in the feeding experiment was accredited to grazing by the snails. In the observation experiment a single snail was kept in captivity for a day with a diet of wheat. The snail was then observed eating the wheat fed to it. 

All results gathered from the preference trials and the feeding experiment have been tested for normality using Lillefors test for normality (not shown). The preference trial results were found to be non-parametric whereas the feeding trial results are normally distributed.

Preference Trials

The snails had three choices of response when placed upon the trial board. Firstly they could stay in the middle (either sitting stationary or moving in circles) or disperse to either a plant grown on a high nutrient solution or a plant grown on a low nutrient solution. To remove any possibility of directional bias the pots were moved around to different positions in the board between trials. Records of which pots the snails moved towards (not shown) and finished at were also recorded for several of the trials (figure 3). Based on these data movement of the snails did not appear to be linked to any directional bias.

The data for time spent in the middle of the trial board, which includes snails that did not moved for the entire trial, (figure 4) showed that the treatment imposed upon the snails before the trial (fed fresh vegetation, fed wheat, starved) significantly affected the amount of time spent in the middle (Kruskal-Wallis, p=0.026, N=60). Figure 4 shows snails fed wheat spent most time in the middle. However figure 5 shows that on average feeding the snails wheat before a trial caused a faster first movement than both the other treatments. This discrepancy is a result of some snails fed wheat not moving for the entire trial. This would have increased the time spent in the middle but not affected the time taken until first movement as there was no first movement. There is a strong relationship between treatment and first movement (Kruskal-Wallis, p=0.014, N=54). The time spent at ‘higher’ and ‘lower’ pots however was shown to not have a relationship with the snail treatments (charts 4 and 5) (Kruskal-Wallis, p= 0.155 (high) and p=0.415 (low), N=60 (for both)).

Figure 3. Pots on which snails were present at the end of each trial. There was no directional bias within the experimental set up which could have affected snail choice.

Figure 4. Comparisons of the time spent in the middle for each treatment. Fresh = fresh vegetation fed to the snails, wheat= wheat fed to the snails, starved= snails were starved for 24hours prior to experiment. Snail treatment has an effect on the amount of time the snails spent in the middle.  
Figure 5. The time taken until the first move for each snail treatment. Treatment type has a strong relationship with time taken until first movement away from the middle.

Figure 6. The time spent at the plants grown on a high nutrient solution for the snail treatment types. Analysis shows that treatment type did not affect the time spent at these plants.

Figure 7. Time spent at the low nutrient treatment plants for the different snail treatments. The treatments imposed on the snails were shown to not affect the time spent at these plants.

Feeding Trial

The feeding trial ran for four days. In this time the snails were left undisturbed and allowed to graze and move at will. The positions of the snails were recorded daily (Table 1). A larger spread of low nutrient treatment plants were visited during the trial. However on average these plants were not frequented by as many snails. It is unclear whether snails stayed at certain pots or made changes in their pot choice. Those not at a pot were either in between specific pots or had managed to find away off the trial board.

                                                                Pot No.
Not at a pot
Table 1.Positions of the sails recorded daily.

On day four the pots were harvested of above ground biomass. This was then dried and subsequently weighed. Comparisons of final masses for the grazed and non-grazed plants (figures 8 and 9) showed that there was a significant difference in weight between the plants that had been grazed upon and those that had not (ANOVA, p=0.018, DF=1). Further analysis of these trends showed that significant difference in mass between the grazed plants (T-test, p=0.038, DF=6) whereas the difference between the un-grazed plants was not significant (T-test, p=0.721, DF=6).

Figure 8. Mass between the grazed plants. The high nutrient treatment plants were significantly heavier than the plants fed a lower nutrient solution.
Figure 9. Mass of the non-grazed plants. The non-grazed plants were not significantly dissimilar in final mass.

The final weights of the grazed and un-grazed replicates (figures 10 and 11) showed that the low nutrient solution plants were not significantly dissimilar in final mass (T-test, p=0.504, DF=6). The high nutrient treatment plants however were significantly different in final weight, with the grazed plants heavier than their un-grazed counterparts (T-test, p=0.008, DF=6).

Figure 10. The final weights of the low nutrient treatment plants. There is no significant difference in final mass.
Figure 11. Final dry mass of high nutrient plants. The differences are significant. 

Temperature and sunlight

The temperature data for the growth glasshouse in which the wheat used in the feeding trial, was grown in (figure 12) shows the wheat to have been grown at a consistent temperature from germination to removal for use.

Figure 12. Temperature data for the growth greenhouse in November. 1= 8/11 the germination date, 2= 29/11 when the wheat was moved from the glasshouse for use.

Charts 11 and 12 show November and December temperatures within the glasshouse used for the preference trial and feeding experiment there was only one low point in temperature at the end of November (no.4 on graph). Charts 13 and 14 show the hours of daylight for the period that the experiments were being run. During this time the shift in daylight hours was not enough to seriously effect plant growth

Figure 13. Temperature data for the trial greenhouse in November. 1=trial of experiment (used 10 snails fed on fresh vegetation, results not shown), 2= first preference trial (starved snails), 3= second preference trial (fed fresh vegetation), 4= third preference trial (starved), first trial to use second wheat batch.

Figure 14. Temperature data for the trial greenhouse in December. 1=fifth trial (fed on wheat), 2=sixth trial (starved), pot order was randomly altered, 3=seventh trial (fed fresh vegetation), start of feeding experiment, 4=end of feeding trial and harvesting of wheat.

Figure 15. Day length for November.

Figure 16. Day length for December.


The first thing to notice is that on the un-grazed board the ‘high’ and the ‘low’ nutrient plants were insignificantly different in final dry mass (means of high-1.086g and low-1.051g). This similarity in mass was most likely a result of the low nutrient solution in fact being too high already and being at the top of the plants growth curve (figure 17).



The time taken till first move was higher for the starved snails than those fed prior to the preference trials (6.42 minutes compared with 3.93 and 3 minutes). This supports Byers (2000) findings on resource availability affecting snail dispersal rates. However the effect of prior feeding on snail pot choice was inconclusive. Either the snails randomly choose which plant they first approach or they could not choose between the ‘high’ or ‘low’ nutrient plants.

Figure 17. The low nutrient solution (the arrow) shown to be a nutrient concentration which was close to the optimal growth of the plant.

Feeding trials

The RAH was upheld in that as predicted the plants grown on high nutrient solution were grazed on more. This grazing corresponded to an increase in final dry mass when compared to the other plants. The non-grazed plants showed no significant difference in final dry mass this most likely due to the low nutrient solution being too high a concentration. However that the masses of the grazed plants were significantly different (high- 1.274g and low- 1.123g) and the un-grazed and grazed ‘high’ plants were also significantly different the only reason for the mass differences must be grazing. Grazers have been shown to increase mass in plants before however (Brown 1994, Agrawal et al. 1999). What is unsure is the specific reasons behind the increase in mass in this experiment. However it has been documented that increase in grazing in grasses has increased above ground biomass (Georgiadis et al. 1989) with an increase in tillering and shoot growth as possible explanations for this. 

Further work

Growth of the plants in a lower concentration low nutrient solution (possibly twice as dilute as the current concentration) and re-running of the preference trials would hopefully both support findings from this project. It would be hoped that the with this change the effect of prior nutrition on the snails preference might show some clear result, if indeed there is a clear result to be had.

With the plants grown at more distinct nutrient treatments the feeding trials should support the findings here. What can be investigated is both tiller number before and after grazing and shoot length before and after grazing. Hopefully this will prove which of these is responsible for the increase in mass observed here.

Another alteration could be too look at the effect of snail age (based on size) on the experiments and by testing snails of similar sizes does this alter the outcomes of the trials.


For the feeding trial RAH was upheld showing that plants growing faster were grazed upon more than slower growing plants. That those plants did no necessarily grow bigger than other plants on offer to the snails before grazing supports this. The increase in mass as a result of the grazing was most likely a result of extra tillering or shoot growth stimulated by the grazing. Preference trial studies showed that dispersal rate increased with prior feeding regimes although actually distinction and choice showed a random pattern.


Without the advice and aid of Mr. Martin Lappage and Miss Chloe Thompson at the University Experimental Gardens and the advice, experience and patience of Dr. David Pilbeam this project would never have been possible. As such my thanks and gratitude goes out to them.


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