Local Environment Europe

The effect of the local environment on bee abundance and diversity in regions throughout Europe.

Bees have an important ecological role; they are insect pollinators providing a crucial service. Without insect pollination human diet would be very different to how we know it now. Declines in pollinators have been reported and by attempting to understand the how the local environment affects bee abundance and diversity it may be possible to prevent any further decline. Samples were collected at six sites across Europe in each site there was a disturbed landscape and a natural landscape and within each of these a hot and a cold area.

Samples were collected, pinned and identified to genera and the Halictus measured. Analysis found that there was no significant difference in size between different countries, landscape and temperature. The number of individuals and the number of genera did not significantly differ between temperature, landscape and country however on a smaller country level there were differences in the numbers of individuals and genera at different landscapes.

The number of bumblebees was affected by the landscape with more individuals found in the disturbed landscapes; it is possible that due to the foraging ability and feeding preferences that bumblebees are able to gain an advantage in a disturbed landscape. Different genera were found in different regions with high numbers of Panurgus and Panurginus found in Spain and Catalunya. The number of bumblebees was also found to be significantly related to latitude. These differences in composition in different areas could be seriously affected in the face of climate change. The effect of the local environment on bee abundance and diversity in regions throughout Europe.

1: Background and importance

“If the bee disappeared off the surface of the globe then man would only have four years of life left. No more bees, no more pollination, no more plants, no more animals, no more man.” Albert Einstein

1.1: The importance of bees

Bees provide the critical ecosystem service of pollination (Kearns et al 1998). Insect pollination is essential for our life as we know it. 84% of crops in the EU depend on insect pollination (Williams 1994) and one third of our diet can be attributed to insect pollination, either directly or indirectly (McGregor 1976). Of the insect pollinators it is bees which provide the most pollination, bees which are highly adapted to flower visitation, have been confirmed to be pollinators for 72.7% of crop species and it is thought they could be responsible for the pollination of another 10.2% (Williams 1994, Roubik 1995).

Declines in bees point towards serious consequences for natural ecosystem process and agricultural processes (Biesmeijer et al 2006). The declines being experienced on local and regional scales present a worrying situation with habitat loss, fragmentation, agricultural intensification and pesticide use causing declines in honey bees, solitary bees, wild bees and bumble bees (Steffan-Dewenter et al 2005).

The greatest diversity of bees in the world is experienced in arid and semi-arid regions of the world including the Mediterranean regions of Southern Europe (Danforth 2007). Most of the bees in the world are solitary bees (National Research Council of the National Academies 2007) and of the solitary bees the majority of them are resource specialists, oligolectic (Wcislo and Cane 1996). Oligolectics are bee species which collect pollen from one genus or species but can collect nectar from a variety of plants, they are often referred to as specialists.

Polylectic bee species are generalists; they can collect pollen from a variety of flowering plants and include the honeybee (Apis) and the bumblebee (Bombus). In theory the risk of extinction is elevated in oligolectic bees as their presence and distribution is limited by just one floral host (Zayed and Packer 2007). Work by Cane et al (2006) into urban habitat fragmentation showed the abundance and richness of oligolectic bees to have declined but not to have declined in the polylectic bees.

Due to the important role of bees it is essential to understand the abundance and diversity of bees across the landscape and the local factors that affect them. By understanding the local factors affecting the diversity and abundance of bees it may be possible to effectively manage and conserve bees and help to prevent any further declines in diversity and abundance.

1.2: Landscape

Much of the natural habitat in Europe has been lost and the habitats with the highest species richness are the remaining semi-natural areas (Pimentel et al 1992).

The impact of disturbance on insect communities is not so extensively studied as the impact on vegetation, on the studies that are available results show that different insect groups respond differently to disturbance (Steffan-Dewenter and Leschke 2003).

Study by Steffan-Dewenter and Leschke (2003) on the effect of habitat management and landscape on bees and wasps in orchards in Europe showed that the vegetation was more significantly affected by the management practices than the insects.

Bee species richness is correlated with the percentage of grassland in the surrounding landscape (Dauber et al 2003, Hendrickx et al 2007, Steffan-Dewenter et al 2002).

The bees in the study by Hendrickx et al (2007) showed not only a decline with distance from semi-natural patches but also a decline with increasing management practices. The other groups in the study experienced increased numbers with proximity to semi-natural habitat but no significant declines with increasing agricultural management. The results for bees can be attributed due to bees having such a strong dependence on floral resources (Tscharntke et al 1998). Low plant diversity with limited floral resources may not to be able to support a high diversity of insects thus resulting in lower insect diversity and the ability to support only the generalist species (Westphal et al 2003).

Proximity to floral resources and nesting sites is important as foraging distances can be fairly small. Large bumblebees such as Bombus terrestris can forage distances up to 3000m, as foraging distances are related to body size, smaller bees may only be able to forage a few metres (Westphal et al 2006). In the tropical forests of Costa Rica pasture management and the floral resources showed to have no significant impact on the diversity or abundance of bees, however deforested countryside just metres away from the forest contained a different community composition (Brosi et al 2006).

The complexity of landscapes means that the impact of disturbance can vary depending on the frequency, intensity and extent of the disturbance (Samways 2005).

Moderate disturbance can actually increase the diversity of the area by opening up areas for colonisation by providing ecological niches and opportunities for rarer species (Caswell 1976, Connell 1978, Petraitis et al 1989). Alternately diversity could be lowered as the dominance of opportunistic species is increased (Margalef 1968).

Bees depend on floral resources for nectar and pollen and can only travel certain distances from their nesting site to reach it, both flowers and nests need to be close by. Therefore declining floral resources, and declining suitable nest sites, as experienced in large scale disturbed areas, may result in the declining numbers and diversity of bees.

1.3: Microclimate- temperature

The microclimate, the lowest two metres of the atmosphere (Stoutjesdijk and Barkman 1992), is the layer of the atmosphere where the majority of plants and animals live (Unwin and Corbet 1991). The soil surface (or other substance, for example forest or concrete) influences the heat and moisture budget of the surrounding atmosphere producing localised variations in the climatic conditions, for example temperature, windspeed and humidity.

The relationship between plant and microclimate is a close one with plants affecting the climatic conditions around them and the microclimate affects the factors controlling the functioning of the plant including the availability of the products required for photosynthesis. Insects benefit from this interaction and due to the close mutalistic relationship between some plant and insect species, for example plants and pollinators, are dependent on a healthy relationship between microclimate and plants. An unsuitable microclimate will lead to the deterioration of plant life and eventual death of the plant and insects dependent on it.

1.4: Insects, temperature and body size

In many insects body temperature is essential in order to gain flight. An insect needs to gain enough energy to fly; it needs to raise the thoracic temperature above the temperature of the environment (Bishop and Armbruster 1999) this can be achieved by basking and endothermy (producing heat in the muscles) (Unwin and Corbet 1991).

The size of the insect plays a vital role in the ability to heat up and subsequently fly and forage. A study by Casey and Joos (1983) found that the proportion of heat lost from the thorax per time unit decreases as the body mass of the insect increases, therefore larger insects are slower at gaining and loosing heat. Bishop and Armbruster (1999) also concluded that the ability to raise temperature in order to fly increases with body size making bumblebees better thermoregulators than solitary bees. Even when looking at solitary bees larger solitary bees will be better at thermoregulation than smaller solitary bees.

Foraging activity can be restricted by thermoregulation factors (Heinrich 1974) and not just over winter. In the summer months foraging at high latitudes and higher temperatures may prove to be difficult for larger insects with solitary bees reaping the floral rewards. Whilst in cooler areas at lower latitudes larger bees, such as bumblebees will have the advantage (Bishop and Armbruster 1999).

Tropical bumblebees have been found to be the largest bees, an exception to the rest of the findings by Peat et al (2205). They found that the mean size of bumblebees varies between different climates with colder climates having a larger mean size than those of warmer climates. Size variation of bumblebees within a region was found not to be related to temperature but other factors, possibly to improve colony foraging with different sizes able to visit different flowers (Peat et al 2005).

It is not just at different temperatures, different latitudes and different elevations that there are heat constraints on the species present but also a daily sequence. Heinrich (1976) observed bees visiting flower patches and noted the day sequence process. Large insects, such as large bumblebees, are able to achieve a body temperature high enough to fly at a lower temperature than a smaller insect, for example a small solitary bee. This then means that earlier in the day the bumblebee can begin to forage and last longer into the evening when the temperature of the environment begins to fall. However in the midday heat the bumblebee may become overheated and need to retreat and cease flying for a few hours. The small solitary bee although not able to start until later and unable to continue into the evening will be able to cope in the midday heat and continue to forage (Unwin and Corbet 1991).

The temperature of the area determines the foraging activity of bees and will influence the bees present in the area. What is under-researched is the effect of very localised temperature has on the bees and size of bees present.

1.5: Climate

The temperature of the environment does not only determine the body temperature of the insect but also the geographical range (Gates 1993). Over the past 30years shifts in the abundance and distribution of a variety of species have been witnessed due to climate change (Parmesan and Yohe 2003). Hickling et al (2006) studied the distributions of different taxonomic groups in Britain over the last 25years to examine any shifts in range that may have occurred. A shift in distribution upwards and northwards was found in most taxonomic groups with the latitude being a more significant factor than elevation.

Alterations to geographic ranges will impact different organisms in different ways and at different times in their lifecycle. It is possible that the interactions between organisms could be severely affected and possibly even destroyed, in some instances resulting in the extinction of one or both of the species. With these shifts in distributions comes the increased possibility of species extinctions, one prediction for 2050 using a mid-range climate scenario showed 15-37% of species committed to extinction (Thomas et al 2004). In order to avoid the risk of extinction species will have to be able to keep up with the changing climate by migrating at fast enough rates however barriers such as mountains and fragmented, disturbed landscapes may hinder this migration (Pearson and Dawson 2003).

General climate models which observe the possible consequences of climate change show a general pattern of the increasing of the Mediterranean summer drought (Gates 1993). As a result it is expected that a shift in species composition will occur and drought conditions will lead to reduced plant cover. This will inevitably impact many insect species including pollinators, such as bees, that will lose their source of nectar and pollen. Research suggests that resource specialists are likely to be the first to suffer declines as they rely on just one plant for their pollen (Cane et al 2006).

Looking at the effect of local temperatures on abundance and richness may be able to give an indication of what will follow with global climate change and thus be an aid for planning and conservation measures.

2: Aims and Objectives

Bees are essential for pollination and are the key to maintaining life as we know it. Reaching and maintaining the right temperature is essential for an insect’s flight, there is evidence that reaching this temperature is related to body size but does it vary with temperature within a microclimate? Does the local temperature affect the bee diversity and abundance and will this provide any insights into what may happen in the face of global climate change? Within Europe it has been reported that it is the remaining semi-natural habitats that contain the most species richness. If this is the case it would be expected that areas of human disturbance would experience a much lower diversity and abundance.

In this project the aim is to examine the effect that the local conditions, temperature and landscape, have on the abundance and genera of bees in a selection of regions across Europe. Within this there are three main objectives to be examined:

• To determine if the local temperature affects the abundance and diversity of bees.

• To determine if the surrounding landscape, disturbed or natural, affects the diversity and abundance of bees.

• To establish whether the size of certain genera are significantly affected by the local environment.

3: Methodology

3.1: Site selection

Samples of pollinators were collected in field sites throughout Europe in the summer of 2007 as part of the CITIRAT (Climate Interactions with Terrestrial plant Interactions a Risk Assessment Tool) project. The CITIRAT project is part of the wider EU ALARM (Assessing LArge scale Risks for biodiversity with tested Methods) project (http://www.alarmproject.net/alarm/). The field sites for the CITIRAT project were pre-determined by ALARM, with the core sites situated in different regions throughout Europe allowing the study of most of the climatic regions in Europe.

For each of the core sites there are two sites measuring 4km by 4km within 50km of each other. One of the two sites being predominantly natural or semi-natural and the other site a disturbed landscape. The two focal sites have being selected so that the geological and environmental parameters are as similar as possible allowing the human disturbance to be the most distinguishing features between the sites. Figure 3.1.1 shows examples of the land cover in each category.

Using GIS analysis the temperature for each of the disturbed and natural areas was calculated using a model which combined the elevation, slope, aspect, average daytime temperature, clear sky solar radiation maps. This model then gave the temperatures for points throughout the landscape, the hottest 10% and coldest 10% of points were selected and ranked, the top two temperature points for both hot and cold were then determined and ready for fieldwork to begin.

3.2: Sampling method

Each of the two landscapes (disturbed and natural) had two sampling rounds approximately 2 weeks apart. Within each sampling round two hot and two cold temperature sites were used (as predetermined by the GIS analysis). Each temperature spot had three cluster sets of pan traps, one white, one yellow and one blue. Each cluster contained five pan traps of a single colour. Each cluster was situated five metres apart in open, low vegetation at ground level. The pan traps were left out over a two day period in dry conditions with low wind and a temperature of greater than 15ºC. Leaving pan traps out over a two day period eradicated any daily variation in bee species present due to daily temperature fluctuations. By using all three coloured pan traps bias was reduced as a range of colour preferences could be catered for (Leong and Thorp 1999).

When the samples, preserved in alcohol, were returned to Leeds the samples were sorted taking note of the number of honeybees, number of bumble bees, number of other bees, number of hoverflies and the number of butterflies. Anything else that was collected in traps was discarded.

The bumblebees and other bees were removed from the sample tubes, and were dried, pinned and labelled. The bees were then identified to genus level and the results recorded.

Figure 3.3.1: Map of Europe showing the ALARM core sites. The yellow dots indicate the sites used in this analysis and their ‘country’ label. Adapted from an image available at: http://www.alarmproject.net.

3.3: Analytical method

Samples were collected at sites all across Europe. Time and resource restraints meant that not all of the sites sampled could be pinned and identified for use in this study. The sites used were carefully selected with sites showing high variation in elevation and therefore temperature differences chosen. Figure 3.3.1 shows the European sites used in this project and table 3.3.1 shows the latitude and longitude of the sites. From here on these ‘sites’ will be called countries to avoid confusion.

To calculate the diversity for each of the conditions at each of the sites the Simpson’s diversity index, which is “one of the most meaningful and robust diversity measures”(Magurran 2004) was used. The index works by calculating the probability, that from a community of infinite size, two individuals will belong to the same species. The Simpson diversity index was expressed as 1-D therefore meaning that as the Simpson’s diversity decreases as does the diversity, this logical adaptation of the index mean that the diversity of the samples could easily be calculated and compared.

In order to determine if the size of bees are affected by the local conditions one genus, Halictus was chosen due to them making up a large proportion of total individuals present. To measure the Halictus samples a random number table was used to determine which specimens should be measured. All of the specimens were females and from two countries, Spain and Germany. Digital callipers were used under a microscope to measure the width of the thorax, in-between the base of the wings.

The numbers of Bombus’ were looked at as well as the size of the Halictus. Bombus’ are known to be (generally) a larger body size and better thermoregulators so provide a good genus to use as an indication of distribution related to the local environment factors.

The information available for use in the statistical analysis was the number of individuals, the number of genera, the temperature (hot or cold), the landscape (disturbed or natural), the country, the sample round (1 or 2), the site (either 1 or 2), the diversity (Simpson’s 1-D), the number of bumblebees, the number of solitary bees and for a selection of sites the size of Halictus.

The statistical analysis was carried out using R and Minitab for the principal component analysis. Excel was used for the production of some of the graphics. Not all the data was normally distributed, distributions were checked using the Shapiro-Wilk test. The analysis used was a mixed effects model but not all data meet the assumptions so where unavoidable non-parametric tests were used, a generalised mixed effects model (glmmPQL).

4: Results

Nineteen Genera were identified; a list of these genera and authorities can be viewed in the appendix A. One genus could not be confirmed despite various opinions but is suspected that it might be Panurginus.

4.1: Individuals and genera

Figure 4.1.1: The mean number of individuals per sample round, error bars indicate ±1 SE.

(t₆₆= -5.804, p=<0.0001, 95%CL)

A mixed effects model was used for the analysis of the individuals. The random effects were site, landscape and country. The standard deviation estimate for country was 0.528 showing that for the countries there was a variation from the mean, this may affect the outcome of the model. The only significant factor was sample round (t₆₆=-6.456, p=<0.001, 95%CL).

There were no significant differences in individuals within temperature, landscape, sample round or any of the interaction terms. To alleviate the problem of countries having a great variation in the numbers of individuals the model was rerun with countries as a fixed factor. This reduced the variation of the random effects and recalculated the fixed effects. Sample round remained the only significant factor (t₆₆= 5.804, p=<0.001, 95%CL) (figure 4.4.1).

The dataset for genera was non-parametric so the model used was the glmmPQL. A very low standard deviation estimate was given for each of the random factors (country=<0.060, site=<0.001) therefore for each of the random effects there is little variation meaning they have little effect on the overall model. There were no significant fixed factors in the model.

4.2: Diversity

The generalised mix effects model for diversity used Simpson’s 1-D values. The estimates of standard deviation for the random effect of country were extremely low, <0.001, showing that for diversity there was almost no variation from the mean (figure 4.1.2). Of the fixed factors for diversity none were significant (95%CL).

Figure 4.1.2: The mean diversity (Simpson’s 1-D) for each country. Error bars indicate ± 1 SE. The diversity was not significantly for any of the factors, Standard deviation between countries was low at <0.001.

4.3: Bumblebees and other bees

The numbers of bumblebees (Bombus spp) were used in a generalised mixed effects model (glmmPQL) in order to determine if there were significant differences in the variation between temperature, landscape and sample round. The standard deviation of country was high at 1.376 showing that within the effect of country there was a lot of variation from the mean, thus contributing to the variation in bumblebees and possibly influencing the overall model. Of the fixed factors sample round and landscape were shown to be significant.

Bumblebee numbers were significantly different for sample round (t₇₉=-3.59, p=0.001, 95%CL) and landscape (t₇₆= -3.314, p=0.001, 95%CL). Rerunning the model with country as a fixed factor changed the results. The standard deviation of the site was low at <0.001 therefore not likely to affect the fixed factors. There were significant differences in landscape (p=0.002, t ₈₁= -3.153, 95%CL), sample round (p=0.001, t₈₁ = -3.394,) and also several countries were significantly different from the control country which was Austria. Catalunya (p=0.001, t₈₁=-3.488, 95% CL), Italy (p=0.043, t₈₁=-2.060, 95%CL), Spain (p=0.014, t₈₁=-2.513, 95%CL) and the UK (p=0.002, t₈₁=3.266, 95% CL). Germany was proven to not be significantly different from Austria (P=0.392, t₈₁=-0.861, 95%CL) (figure 4.3.3).

Figure 4.3.2: The number of bumblebees per landscape. Error bars indicate ± 1SE (t₈₁=-3.153, p=0.002, 95%CL).

Figure 4.3.1: The number of bumblebees per sample round. Error bars indicate ± 1SE (t₈₁=-3.394, p=0.001, 95%CL).

Figure 4.3.3: The mean number of bumblebees per country, error bars represents ± 1 SE.

The number of other bees (bees that were not honeybee or bumblebees) were taken and used in a mixed effect generalised linear model (glmmPQL). The model was initially run with the random factors of country and site. The standard deviation for country was 0.968