Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes)

Accepted Manuscript Title: Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes) Author: Weronika Banaszak-Cibicka Halina Raty´nska Łukasz Dylewski PII: DOI: Reference:

S1618-8667(16)30361-2 http://dx.doi.org/doi:10.1016/j.ufug.2016.10.015 UFUG 25801

To appear in: Received date: Revised date: Accepted date:

29-8-2016 25-10-2016 25-10-2016

Please cite this article as: Banaszak-Cibicka, Weronika, Raty´nska, Halina, Dylewski, Łukasz, Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes).Urban Forestry and Urban Greening http://dx.doi.org/10.1016/j.ufug.2016.10.015 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes)

Weronika BANASZAK-CIBICKA1, Halina RATYŃSKA2, Łukasz DYLEWSKI1

1

Institute of Zoology, Poznań University of Life Sciences, Wojska Polskiego 71C, 60-625 Poznań, Poland, e-mail: [email protected]

2

Institute of Environmental Biology, Kazimierz Wielki University, Ossolińskich 12, 85-093 Bydgoszcz, Poland

1

Features of urban green space favourable for large and diverse bee populations (Hymenoptera: Apoidea: Apiformes)

Abstract

Cities are habitats created almost exclusively for a single species, Homo sapiens. However, the mosaic-like character of urban environments may create favourable living conditions for various populations of bees. Due to the negative impact of intensified agriculture and landscape fragmentation on pollinator insects, interest in urban areas as refuges for local bee fauna is growing. The author’s three-year research has shown that the distance of a bee community from a large green space with direct connection to suburban areas is the decisive factor for bee species richness in a city. The proximity of such green space areas facilities penetration of species into cities. As for the density of bees in the urban environment, it was largely determined by host plant cover. These data are of practical importance, as they may be used in future urban green space planning.

Key words: wild bees, vegetation composition, cities, invertebrates

2

1. Introduction

Bees are a unique group of insects as they play a major role in plant pollination due to their absolute dependence on flowers as the source of food (Bond 1994; Vamosi et al. 2006; Klein et al. 2007). Unfortunately, there is clear evidence of recent global declines in both wild and domesticated pollinators (Potts et al. 2010). Environmental protection to date has concerned mostly areas that are either natural or scarcely modified by humans. Yet in view of the fact that bees are important pollinators of cultivated plants, focus has also been placed on increasing the quality of agricultural landscapes in order to ensure favourable conditions for these insects. Well-managed agroecosystems with a mosaic structure increase the abundance and diversity of pollinating insects, which, in turn, enhances crop production (Richards 2001; Ricketts et al. 2008; Garibaldi et al. 2013). However, the widespread intensification of agriculture and the growth in cultivation area acreage are still thought to be two important reasons for the loss of biodiversity in agricultural landscapes (Kremen et al. 2002; Tscharntke et al. 2005; Carvell et al. 2006). Cities are habitats created almost exclusively for a single species, Homo sapiens, and many researchers point to urbanisation as the reason behind the disappearance of a significant number of animals and plants (Jackowiak 1998; Czech et al. 2000; McKinney 2008; Jones and Leather 2012). On the other hand, high heterogeneity of the urban environment allows occurrence of species with various habitat requirements and creates exceptionally good living conditions for certain species (Luniak et al. 1990; Langowska et al. 2010; Møller et al. 2012; Banaszak-Cibicka 2014). There is ample evidence that cities are appropriate habitats for a 3

significant number of bee species (Saure 1996; Zapparoli 1997; Cane 2005; Frankie et al. 2005; Banaszak-Cibicka and Żmihorski 2012), which are not affected by the urbanisation pressure as negatively as many other insects (Deguines et al. 2012). Green areas in cities are growing in importance as refuges for local bee fauna in the context of the increasingly intensive agriculture, which negatively affects the fauna in agricultural areas, and due to the relatively low proportion of landscapes where human impact is minimal (Zerbe et al. 2003; Miller 2005). Urban nature is beneficial for city inhabitants since contact with nature contributes to human health (De Vries et al. 2003) and general well-being (Fuller et al. 2007). At the same time, urban green areas of different types may influence the pollinator insect fauna in different ways. Therefore, it is crucial to explore the impact of different urban areas and their plant cover on the development of bee populations that inhabit these areas or visit them to forage. There are fewer publications on bee communities in urban and suburban habitats than on bees in agricultural and wildland settings. The same tendency apply to research on relationships between bees and vegetation (Hennig and Ghazoul 2011). The aim of this study was to establish which properties of green areas contribute to increased species diversity and abundance of bees. We investigated to what extent bee communities are influenced by plant structure and species composition and by the distance from larger green areas directly connected with more natural suburban areas.

2. Methods

2.1. Study area

4

The study was carried out in the city of Poznań, Poland (52˚25’N, 16˚58’E), whose population amounts to 560,000 residents. Bees were sampled on eight sites (50×50 m) located within the urban matrix representing a wide spectrum of urban environments. For this purpose we selected large green areas, potentially available for many bee species with the aim of identifying the full set of species present in the city. Study plots were located along the urbanization gradient: green spaces in closely built-up areas with tenement houses in the city centre, loosely built-up housing estates with detached houses, and large urban green areas. The study sites were located from 250 to 4,900 m from the city centre. The sites also varied in their distance from larger urban green spaces directly connected with suburban areas (Table1). Another variable was the covering vegetation: The garden behind the church surrounded by concentrated settlement of tenement houses (CS1); The garden in front of The Museum of Utilitary Art in the Royal Castle surrounded by concentrated settlement of tenement houses (CS2); Green area between concentrated settlement of tenement houses (CS3); River meadow close to concentrated settlements (RV); Botanical Garden (BG); Dendrological Garden (DG); Green area in a sparse housing estate (HE); and Home garden located in a district of detached houses (HG). A map with detailed distribution of the sites is to be found in Banaszak-Cibicka and Żmihorski (2012). Every study site was described with regard to its covering by trees, shrubs and herbaceous plants. We compiled complete lists of vascular plant species found in the study plots and estimated the distance of the plot from larger urban green spaces with a direct connection to more natural areas outside the city.

2.2. Bee sampling

5

Research was conducted for three years between April and September. Two methods were used to collect bees: yellow bowl traps and hand-netting. Four traps were placed in every plot and the captured insects were removed from the traps every 7-10 days (Banaszak et al. 2014). The gathered specimens were identified to species level. Direct searching along transects, was also conducted at each site. In order to estimate bee density in the study plots, sampling was performed using the belt transect method developed by Banaszak (1980). The method involves counting and capturing insects with an insect net from a 200 long and 1 m wide belt in weather conditions favourable for bee flights, i.e. between 10 am and 4 pm, with low or no wind, and minimum air temperature of 20°C. The observed density of bees was calculated per 1 ha. Bees were netted by hand twice each month from April to September.

2.3. Vegetation structure

Vascular plant flora was listed at each study site. In order for the list of plants to be as complete as possible, the first field research took place in spring and the second at the height of the vegetation season. The cover-abundance of plant species was assessed using the commonly accepted Braun-Blanquet scale where: r – solitary individuals of a species + – very few individuals of a species 1

– few individuals with cover <5%

2

– 5.1-25% cover of total plot area

3

– 25.1-50% cover of total plot area

4

– 50.1-75% cover of total plot area

5

– 75.1-100% cover of total plot area. 6

The species were also characterised according to the pollination mechanism, in particular with regard to insect, wind, and self-pollination. The nomenclature employed follows Rutkowski (1998), Marcinkowski (2002), and Throll (2009). In order to assess the degree of modification due to human activity in every study site, we also measured the percentage of land covered with human-made structures, such as buildings, streets, and parking lots within 500 m radius from the study site centre (Table 1). This feature is used frequently as an urbanisation index (McIntyre and Hostetler 2001; McKinney 2002; Ahrné 2008).

2.3. Statistical analysis

Colwell’s method (1997) was used to establish if the collected samples were sufficiently homogeneous to estimate the total number of species in the area investigated. The method involves comparing sample-based species accumulation curve with Coleman’s curve (Coleman 1981; Coleman et al. 1982). The representativeness of the faunal material was evaluated with the use of nonparametric species richness estimator Chao1 (Chao 1984, 1987). The number of species was estimated with EstimateS software (Colwell 1997). Distributions were measured prior to the analyses. No distribution of values deviated significantly from the normal distribution (Kolmogorov–Smirnov test, test values for the parameter closest to the normal distribution: K-S = 0.871; P = 0.433). Thus, the relationships between environmental features and species richness and density of insects could be analysed with parametric tests.

7

Correlation and regression analyses were also conducted. Firstly, a correlation matrix of all independent factors describing the environment was prepared: percentage of tree cover – TREES, percentage of shrub cover – SHRUBS, percentage of undergrowth cover – UNDERGR, the total number of plant species recorded in the reference area – PLANT_SPEC, the number of host plant species – HOST_SPEC, the percentage of host plant cover – HOST_COV, distance from larger green space directly connected with suburban areas (m) – DIS_SPACE, distance to the city centre (m) - DIS_CENTRE, the percentage of land covered with man-made structures within 500 m radius from yellow bowl traps – BUILT 500, and the number of bee species – N_SPEC and mean bee density in the study plots – BEE_DENS. For this analysis we used Spearman rank-order correlation because of the small sample n=8. The descriptive statistics summarizing mean, standard error and 95% confidence intervals (95% CI) on variables are presented in Table 2. A simple interpretation of the correlation matrix (Table 3) shows that environmental parameters were strongly correlated. Therefore, the analyses which include the relations between these parameters are more correct. The analysis method chosen was stepwise regression. The environmental features chosen for the analysis were the ones believed to be most important for pollinators (Cierzniak 2003; Ahrné 2008). Further analyses were limited to 5 parameters: UNDERGR, HOST_SPEC, HOST_COV, DIS_SPACE, and BUILT 500. Prior to the analyses the percentage values of the parameters were transformed by arcsin while the distances were transformed by log10. The bee density dependent variable was also transformed (log10) prior to the regression analysis. All computations were performed in the SPSS 20.0 statistical package (www.spss.pl).

3. Results 8

3.1. Species composition

In the course of the study 2,495 individuals belonging to 104 bee species were captured in the city of Poznań (full list of species in Banaszak-Cibicka and Żmihorski 2012). The Chao1 species richness estimator, corrected for unseen species in the samples, suggested 124 species. Bee density in Poznań ranged from 247 indiv/ha in the tenement houses area to 614 indiv/ha in the Botanical Garden.

3.2. Bee–vegetation relationships

Based on the calculated correlation indices we distinguished those features of the study plots that had a significant impact on the species richness and abundance of bees. A strong significant positive correlation was found between plant species richness and density of bees (rho = 0.74, P<0.05) and between bee density and host plant cover (rho = 0.81, P<0.05). A strong significant negative correlation was found between species richness and distance to larger green spaces directly connected with suburban areas (rho = -0.78, P<0.05). In case of density of bees we also found a significant negative correlation between cover of built up areas (rho = -0.77, P<0.01). The other correlations for study variables was presented in Table 3. Multiple regression showed that the number of bee species was statistically dependent only on the logarithm of distance from larger green spaces (B = -29.22 ± 7.44, t = -3.93, R2 = 72.0%, P = 0.008). This variable explains the 72% variance of species richness of bees in the built-up areas investigated (Fig. 1). 9

Mean density of bees (log10 prior to analysis) was statistically dependent only on the host plant cover (B = 0.59 ± 0.15, t = 3.98, R2 = 72.5%, P = 0.007). This variable explains the 72.5% density variance in the built-up areas investigated (Fig. 2)

4. Discussion

The regression analysis demonstrated that the distance of a bee community from a larger green space with direct connection to suburban areas is the decisive factor in bee species richness in a city. Suburban areas supply urbanised environments with species. Close proximity of larger green spaces connected with suburban areas facilitates the penetration of species into city interiors and species exchange between populations. The usual distribution of green spaces in cities is not linear, and the larger the distances between scattered parks and gardens, the more difficult it likely is for bees to move between areas. This is particularly true for small species of bees that do not cover large distances in order to collect food, find appropriate nesting sites, or perform nuptial flights. Since flight range depends on body size (Westrich 1989; Wessering and Tscharntke 1995; Greenleaf et al. 2007), flight ranges vary across species (Gathmann and Tscharntke 2002; Knight et al. 2005). Consequently, each species will be differently affected by the distance between favourable habitats. Connection between habitats is considered by many authors to be a significant factor for increasing biodiversity (Niemelä 1999; Savard et al. 2000; Melles et al. 2003). Mean density of bees in the city was 438.5 indiv/ha, which may be considered a relatively high abundance of bee communities. By way of comparison, the bee density in the oak-hornbeam forests of Wielkopolska National Park situated 15 km south from Poznań 10

ranged from 64 to 100 indiv/ha, while in house gardens in the vicinity of the National Park the abundance of bees was 564.2 indiv/ha (Cierzniak 2003). Our study has demonstrated that the density of bees in urban environment depends primarily on host plant cover. An abundant cover of host plants creates an appropriate food base for bees and favourable conditions for their higher density. Many researchers believe it to be a fundamental factor affecting the density of bees (Banaszak 1983; Cierzniak 1994; Banaszak and Cierzniak 2000; Calabuig 2000; Steffan-Dwenter and Tscharntke 2000; Frankie et al. 2005; Ahrné 2008; Frankie et al. 2009; Kearns and Oliveras 2009). Plant species diversity was less influential on species richness and abundance of bees in our study. The same has been concluded by Cierzniak (2003). It is undoubtedly connected with the fact that some plant species are not attractive to bees and do not comprise a source of food. Moreover, as the vast majority of Apidae species observed in Poznań are polylectic species able to collect pollen from various plants, the occurrence of a particular plant species is not especially important to these insects. What is important is high cover of host plants. Negative correlations between the density of bees and the cover of shrubs and undergrowth most probably arose from a reduced area available for nesting. Dense undergrowth vegetation makes it difficult or impossible for ground-nesting species to build their nests. Likewise, sites under shrubs are not appropriate for nesting, due to deep shade and high humidity. The majority of species recorded in the city were ground-nesting species (60%). A lack of suitable soil substrates for nesting and/or hibernation may be a major cause of poor bee diversity and abundance (Jacob-Remacle 1984; Goulson et al. 2002). The results of the study are of a high practical importance, as they can be used for future urban green space planning. Flowering plants are a dominant mechanism for structuring bee communities because bees depend upon flowers for food and nest provisioning. Providing 11

abundant floral resources can help sustaining dense local pollinator populations. Besides the high cover of host plants, nesting locations are also important. Since the majority of native bees do nest in the ground urban green areas with a variety of landscape features including patches of bare soil can assure appropriate nest habitat. What is more, the importance of habitat connectivity in the urban landscape has also been demonstrated. Minimising isolation between parks, gardens and suburban areas will result in benefits to urban biodiversity. Overall, with an appropriate urban planning and proper management, green spaces can be made more attractive to pollinator insects and thus increase their species richness and abundance.

5. Conclusions

1. The distance of a bee community from a larger green space with direct connection to suburban areas was the decisive factor for bee species richness in a city of Poznań. Proximity of such areas may facilitate the penetration of species into cities. 2. The density of bees in this urban environment depended primarily on the host plant cover. An abundant cover of host plants creates an appropriate food base for bees and favourable conditions for their higher density. 3. The study found a negative correlation between the density of bees and shrub and undergrowth cover. This is related to the high proportion of ground-nesting bee species, for whom dense shrub and undergrowth cover means reduced nesting area.

6. Acknowledgments 12

We acknowledge the gracious hospitality of all landowners for allowing us to collect data on their property. Anonymous reviewers provided helpful comments on the previous version of the text.

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Fig. 1 The relation between bee species richness in the study plots and the distance of the plot from larger green space with direct connection to suburban areas.

Fig. 2 The relation between mean density of bees in the study plots and the percentage of host plant cover.

19

Table 1 Characteristics of the eight plots.

No.

Plot

1 2 3 4 5 6 7 8

CS1 CS2 CS3 RV BG DG HE HG

% built up areas r=500m 80 90 70 50 30 40 20 15

% trees, r=500 5 5 10 5 25 20 40 30

% green, r=500 10 10 20 35 50 50 65 70

Distance to centre [m] 250 700 1800 1050 2730 4900 3420 3480

Table 2 Descriptive statistics summarizing mean, standard error, range, and 95% confidence intervals (95% CI) on variables. Variables (units) Built up area (%) Distance to center (m) Distance to bigger green area (m) Undergrowth cover (%) Tree cover (%) Number of plant species Number of insect pollinated species Insect pollinated species cover (%) Shrub cover (%)

Mean (SE) 43.75(10.89) 2291.25(569.56) 1906.25(462.76) 81.88(4.53) 16.25(3.37) 99.75(8.76) 68.63(7.26) 59.38(4.58) 18.75(2.06)

Min-Max 15-90 250-4900 300-3700 60-95 5-30 64-127 32-91 40-80 10-30 20

95% CI 18.01-69-49 944.46-3638.04 812.00-3000.50 71.17-92.58 8.27-24.23 79.05-120-45 51.46-85.79 48.56-70.19 13.88-23.62

Table 3 The Spearman correlation matrix of study variables. * correlation is significant at the 0.05 level, ** correlation is significant at the 0.01 level. BUILT 500

TREES

SHRUBS

UNDERGR

Distance to centre (m)

DIS_SPACE

PLANT_SPEC

HOST_SPEC

HOST_COV

N_SPEC

BUILT 500

1.000

TREES

-0.194

1.000

SHRUBS

0.559

0.372

1.000

UNDERGR

0.529

0.000

0.510

1.000

DIS_CENTRE

-0.802*

0.540

-0.166

-0.401

1.000

DIS_SPACE

0.802*

-0.154

0.434

0.601

-0.857**

1.000

PLANT_SPEC

0.311

0.000

-0.230

-0.401

-0.333

0.071

1.000

HOST_SPEC

-0.347

0.154

-0.639

-0.451

0.262

-0.500

0.667

1.000

HOST_COV

-0.539

0.039

-0.788*

-0.431

0.301

-0.518

0.422

0.916**

1.000

N_SPEC

-0.699

-0.078

-0.629

-0.554

0.623

-0.778*

-0.084

0.479

0.667

1.000

BEE_DENS

-0.766*

0.000

-0.702

-0.651

0.405

-0.571

0.143

0.595

0.807*

0.743*

BEE_DENS

1.000

BUILT 500 - the percentage of land covered with man-made structures within 500 m radius from yellow bowl traps (built up area), TREES - percentage of tree cover, SHRUBS - percentage of shrub cover, UNDERGR - percentage of undergrowth cover, DIS_CENTRE - distance to the city centre (m), DIS_SPACE - distance from larger green space directly connected with suburban areas (m), PLANT_SPEC - the total number of plant species recorded in the reference area, HOST_SPEC - the number of host plant species, HOST_COV - the percentage of host plant cover, N_SPEC - the number of bee species, BEE_DENS - mean bee density in the study plots.

21

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