Forest Ecology and Management 258 (2009) 1838–1845

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Forest Ecology and Management

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Nearby rainforest promotes coffee pollination by increasing spatio-temporal stability in species richness

Alexandra-Maria Klein 1,*

Agroecology, University of Goettingen, Waldweg 26, 37073 Goettingen, Germany

ARTICLE INFO ABSTRACT

Article history: Natural tropical forests are highly diverse and are known to contribute to forest-based services such as Received 16 November 2008 pollination of nearby crops. Landscape changes cause spatial and temporal bee community changes, but Received in revised form 2 May 2009 consequences how the community changes affect pollination is not well analyzed. This paper addresses Accepted 9 May 2009 the effects of rainforest distance and on site flower resources in agro-forests on spatial and temporal variation in pollinator communities and the consequences for coffee pollination. Keywords: The study was conducted in 24 agro-forests dominated by coffee and cacao in Sulawesi, Indonesia Community stability differing in their distance to rainforest margin of the Lore-Lindu National Park and in flower density and Forest-based regulating services its temporal variation. In all agro-forests, (1) transect surveys of the understory were obtained over a Pollination services Resource heterogeneity five-month period to assess bee community compositional similarity, bee diversity, and the temporal variation in bee diversity; and (2) coffee flower visitors were observed and open and bagged pollination treatments conducted over one week of coffee blooming to assess bee diversity and the spatial variation in bee diversity and coffee pollination. Mean number of shared species of the understory ranged between 40 and 60% per agro-forest and was higher in agro-forests nearby the rainforest than in agro-forests with a minimal distance of 500 m isolated from the rainforest. Mean species richness in the understory and in coffee flowers decreased with rainforest isolation and increased with flower resource availability. Temporal variation in bee species richness of the understory and spatial variation of the coffee flower-visiting bee species richness per agro-forest increased with forest distance. The variation in bee species richness decreased the mean and increased the spatial variation in bee-pollinated coffee fruit set per agro-forest. In conclusion, crops grown near intact rainforests and which profit from the pollination by many species may fluctuate less in bee-pollinated fruit set across crop plants than crop plants in isolated agriculture that receive low or even single species pollination services. ß 2009 Elsevier B.V. All rights reserved.

1. Introduction between agriculture and forest with consequences for pollinators depending on forest resources like for nesting (Klein et al., 2008). The majority of tropical and global crops benefits by The increasing distance to semi-natural and natural habitats is pollination (Roubik, 1995; Klein et al., 2007) and land used to grow described to decrease wild pollinator diversity and flower-visiting pollinator-dependent crops increased during the last five decades frequency (Ricketts et al., 2008). This decay in pollinator diversity (Aizen et al., 2008). This trend in agriculture to favor pollinator- and flower-visiting frequency with increasing distance to natural dependent crops indicates an increasing need of pollinators in habitat was found to be especially strong in tropical areas (Ricketts agriculture and an increasing transformation of tropical forests to et al., 2008). Hence negative effects of habitat transformation on agriculture (Aizen et al., 2008). The conversion of natural rainforest crop pollination in tropical countrysides may be stronger than in to land use systems is described as the most important driver of temperate countrysides (Ricketts et al., 2008). decreases in global biodiversity in terrestrial habitats (Sala et al., Not all bee species are equally and negatively affected by 2000). Deforestation will ultimately increase the distances rainforest destruction. Most susceptible are small, stingless eu- social bee species such as members of the family Meliponinae that often nest in high trees (Roubik, 1988; Heard, 1999; Brown and Albrecht, 2001; Slaa et al., 2006; Brosi et al., 2008). Less affected are * Tel.: +49 551 3922257; fax: +49 551 398806. E-mail address: [email protected]. some large-bodied cavity-nesting that can fly long distances 1 Environmental Sciences Policy and Management, 137 Mulford Hall, University to forage and are therefore less sensitive to rainforest loss (Klein of California in Berkeley, CA 94720-3114, USA. et al., 2008). Yet other bees may prosper in agricultural landscapes

0378-1127/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2009.05.005 A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845 1839 because of the increasing availability of bare and dry soil for ground cover (this paper explicitly addressed the effects of rainforest nesting (Shuler et al., 2005), the high availability of crop flower distance and flower density; for details on the measurement of other resources (Westphal et al., 2003; Herrmann et al., 2007), or by high habitat variables see electronic Appendix). The distances between plant diversity and high overall flower density for foraging (Klein each agro-forest and the rainforest margin were measured with a et al., 2003; Ebeling et al., 2008). Global Positioning System (GPS 12 from Garmin, Olathe, Kansas, These different responses of species to environmental changes USA). Flower density was estimated by sight as the percentage cover can produce compensatory dynamics among species with respect of actual flower corollas per area ground surface within 50 m 200 m to relative abundances, but species richness and especially species in the middle of each agro-forest after each of the five transect identity and community similarly often change in changing surveys. The arithmetic mean of flower density per agro-forest across environments (Klein et al., in press). Changes in pollinator diversity the five temporally separated surveys was calculated. As a measure of caused by changes in the availability of pollinator habitat and temporal variation in flower density of the bee’s food resources on resources are described to affect coffee pollination (Klein et al., site, the Coefficient of Variation (CV = ratio of the standard deviation 2003; Klein et al., 2008; Vergara and Badano, 2008). Even more, to the mean in percent) was calculated to measure the dispersion of a variation in coffee flower density can affect the relationship of bee probability distribution in flower density per agro-forest and was diversity and coffee pollination (Tylianakis et al., 2008). used in the statistical analyses. Trees were not in bloom in the studied High bee diversity is also important because it can spatially agro-forests during the time of the surveys. (Klein et al., 2003,in press) and temporally stabilize (Kremen et al., 2004; Ebeling et al., 2008) pollination services by reducing the 2.2. Bee understory transect surveys outside coffee blooming mean variation in flower visitation or pollination per site. Despite this knowledge, there is today no study available showing both Transect surveys of the understory to measure temporal spatial and temporal variation in bee species richness of the same variation in bee (: Apocrita, Apoidea, Apiformes) study area and sites and whether these spatio-temporal changes species richness and abundance per agro-forest were conducted are responsible for variation in pollination services among crop every two to three weeks from early November to end December in plants. 2000 and from mid January to early February in 2001 directly Ecological stability is described in multiple ways but many before and after the 15 days of blooming coffee plants. Conse- studies measure stability as the reverse of the Coefficient of quently, the observations of coffee flowers were temporally Variation between samples (CV) (Griffin et al., in press). This study separated from the transect surveys, but also carried out in the measures two facets of bee community stability in relation to wet season. Bee species richness and abundance were measured rainforest isolation, flower density, and temporal variation (CV) in using visual counts along five temporally separated randomized flower density; (i) temporal variation (CV) in the understory bee 200 m transect surveys per agro-forest on sunny days with low species richness and abundance sampled at different times outside wind speed (below three Beaufort) between 09.00 and 14.00 h. the period when coffee blooms, and (ii) spatial variation (CV) in Observations were conducted for 30 min per transect and were species richness and abundance of bees foraging on individual interspersed among agro-forests and days. Bees were usually coffee plants during the bloom period. Specifically, this study identified whilst visiting herb and understory crop flowers. Bee focuses on the following three questions: (1) Does the mean species that could not be identified whilst searching or perching number of shared bee species change with increasing rainforest were caught and, if necessary, collected and prepared for further isolation? (2) Do the temporal variation in bee species richness and identification in the laboratory. The arithmetic mean of bee species in abundance decrease with increasing rainforest isolation, richness and abundance per agro-forest across the five temporally decreasing flower density, and temporal variation in flower separated transect surveys and the Coefficient of Variation (CV) in density? (3) Do spatial and temporal variation in bee species understory bee species richness and abundance per agro-forest richness and abundance reflect spatial variation in bee pollination was calculated and used in further analyses. of coffee? The results will help to understand variability in bee-pollinated 2.3. Bee coffee flower visitor surveys and coffee pollination services fruit set among plants. Observations of flower-visiting bees foraging at highland coffee 2. Materials and methods flowers, Coffea arabica L., were conducted between 26 December 2000 and 9 January 2001. At each agro-forest, flower-visiting bee 2.1. Study area, study sites, and habitat characteristics species richness and abundance were observed for 25 min on three consecutive days. Every day another full blooming coffee plant The study was conducted in November 2000 to early March with fresh flowers, comprising a total of three plants, was observed 2001 in 24 coffee agro-forests in Central Sulawesi (Indonesia, in the middle of each agro-forest with a distance to previously 1224–1299 m, 018240S 1208200E) in the vicinity of the Lore-Lindu selected plants of at least 20 meters under standardized weather National Park (Napu valley), 100 km southwest the city of Palu (see conditions. Mean values and spatial variation in species richness Klein et al., 2006 for a detailed map of study site arrangement and and abundance among the three individual plants were calculated land use classification). The 24 agro-forests were dominated by (detailed methodology see Klein et al., 2003). The arithmetic mean coffee, some were intercropped with cacao, and many included of bee species richness and abundance per agro-forest across the patches of annual crops or single perennial trees or shrubs that three coffee plants and the CV in flower-visiting bee species were mainly used to nourish the farmer’s family. The agro-forests richness and abundance per agro-forest was calculated and used in differed within the following habitat variables: distance to the further analyses. margin of the continuous natural rainforest (mean SD: In addition, fruit set on four coffee plants per agro-forest was 364.58 369.87, range: 0–1415 m) and the density of ground cover measured to analyze spatial variation in bee pollination provided plants that were bearing flowers at the time of the study (mean flower to coffee plants. One branch per plant was selected for each density SD: 8.65, 11.34, range: 0.01–41%). These two variables treatment. Bee pollination per plant was expressed as the were not significantly correlated, but shade level measured as light difference of initial fruit set of the branch with the open, bee- intensity (mean SD: 371.84 278.75, range: 37.5–899.6 W/m2) pollinated flowers minus the branch of the bagged flowers to were significantly and positively related to flower density in the account for autonomous self-pollination. Mean values and spatial 1840 A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845 variation (CV) per agro-forest were calculated for the four coffee pollinated fruit set (open minus bagged pollination) and spatial plants per agro-forest. For the bee surveys, coffee plants were variation in bee-pollinated fruit set per agro-forest. The variables selected next to the experimental plants that were used to measure flower density, temporal variation in flower density, mean species the bee’s impact on pollination. richness and abundance of the transect surveys and mean abundance of the flower-visitor surveys per agro-forest were 2.4. Statistics log-transformed, distance to the rainforest was square-root transformed, to meet assumptions of normality. All other tested Species saturation curves were estimated using ACE (abun- variables showed normal distribution. dance-based Coverage Estimator of the number of bee species) for the transect surveys and the flower-visitor surveys for each agro- 3. Results forest using 100 randomizations (EstimateS, version 8.0 for Windows, Colwell, 2006). The proportion of sampled to expected 3.1. Bee community composition and similarity in the understory bee species richness (calculated by EstimateS) for each agro-forest transect surveys were calculated (for results on the flower-visitor surveys see Klein et al., 2003). The Chao’s abundance-based Jaccard similarity index Almost 4000 individual bees distributed among 52 bee species (herein after reffered to Jaccard index) was used to account for the were observed during 3600 min of transect surveys (Table 2). overlap of species between sampled days of the transect surveys Species richness per agro-forest was on average 90.25 1.9%, per agro-forest (Chao et al., 2005). The Jaccard index was calculated n = 24, of the estimated species richness. The bee community between each pairs of two samples of the five transect surveys per included seven eu-social bee species with 1683 individuals (65% agro-forest using EstimateS. All other analyses were performed honey bees, 35% stingless bees), and 45 solitary bee species with 2288 using the R, version 2.8.1 for Windows (R Development Core Team, individuals, including semi-social ‘‘sweat bee’’ species. 2009). The Jaccard index of the bee species communities in the agro- Mean numbers per agro-forest were calucalated to avoid the forests ranged from about 40 to 60% per agro-forest and was only problem of pseudo-replications as transect surveys were all done marginally related to rainforest distance (P = 0.0800, R = 0.37). at the same corridor per agro-forest. The Jaccard index was However, the classification of agro-forests in three forest distance normally distributed and the relationship between the Jaccard categories (0–50 m, 50–500 m, 500–1600 m) showed that the index and rainforest distance was tested in a simple regression and communities at the rainforest margin were significantly more one-way ANOVA using the following categories for forest distance: similar than communities in agro-forests 500–1600 m away from 0–50 m, 50–500 m, 500–1600 m. the rainforest (Fig. 1). The response variables, bee species richness, abundance, and the temporal variation (CV) in bee species richness and abundance 3.2. Bee diversity and its temporal stability in the understory transect of the transect surveys were tested in relation to the habitat surveys variables rainforest distance, flower density, and temporal variation (CV) in flower density per agro-forest using generalized Mean flower density and rainforest distance significantly or general linear models. Generalized linear models were affected the mean bee species richness per agro-forest (Table 1, conduced assuming Poisson distribution for bee species richness Fig. 2A), but the temporal variation in flower density did not and negative binominal distribution for bee abundance using the (Table 1). The final model was similar for the mean abundance per library MASS. General linear models were used to test for agro-forest (Table 1). Both models for the mean species richness relationships of the temporal variation in bee species richness and abundance per agro-forest showed that the mean species and abundance with the habitat variables rainforest distance, richness and abundance decreased with increasing rainforest flower density, and temporal variation (CV) in flower density per distance and increased with increasing mean flower density per agro-forest. The AICc (corrected Akaike Information Criterion) was agro-forest (Table 1). used in selecting the best-fitted models (models with lowest AICc). Rainforest distance only explained the temporal variation in This was done as the ratio of the number of replicates to the bee species richness per agro-forest. The temporal variation in number of explanatory variables in all models were smaller than 40 (Burnham and Anderson, 2002). AICc were calculated by the non-corrected AIC + (2k (k + 1)/n k 1), with k = the number of explanatory variables in the model and n = the number of replicates. Models with interaction terms are not presented as those models showed never lower AICc than the best-fitted model without interaction terms. Generalized linear models assuming Poisson or negative bionminal distribution were also applied to test for relationships of mean single species abundance with rainforest distance, flower density, and temporal variation in flower density per agro-forest. A Pearson correlation matrix was used to test the simple relationships between the habitat variables rainforest distance, flower density, and temporal variation (CV) in flower density per agro-forest with bee community variables of the transect surveys, the coffee flower-visiting surveys, and bee-pollinated coffee fruit set. Following variables of the transect surveys were tested: mean bee species richness and abundance, mean Jaccard index, temporal variation in bee species richness and abundance per agro-forest.

Following variables of the coffee flower-visiting surveys and coffee Fig. 1. The mean Jaccard index per agro-forest in relation to three categories of pollination were tested: mean bee species richness and abundance, forest distance: 0–50 m, 50–500 m, 500–1600 m. F = 3.10, P = 0.0468. Letters spatial variation in bee species richness and abundance and bee- indicate significant differences between groups identified by multiple range tests. A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845 1841

Table 1 Results of general or generalized linear model analyses testing for the effects of mean bee species richness, mean abundance and temporal variation (CV) in bee species richness and abundance on rainforest distance, mean flower density, and temporal variation (CV) in mean flower density. Models are presented in the order of the lowest AICc and models with lowest AICc are highlighted in bold.

Response variables Explanatory variables P Direction Residual Deviance AICc

Mean bee species richness Rainforest distance (m) ** 38.70 Flower density (%) *** + 14.12 128.28 Rainforest distance (m) ** 38.70 Flower density (%) *** + 14.17 CV Flower density ns 14.16 130.90 Flower density (%) *** + 23.79 CV Flower density ns 22.01 136.11 Flower density (%) *** + 23.79 135.51 Rainforest distance (m) *** 38.70 150.42 Rainforest distance (m) *** + 38.70 CV Flower density ns 37.30 151.46 CV Flower density ns 63.92 175.63

Mean bee abundance Rainforest distance (m) ** 53.83 Flower density (%) *** + 24.57 258.61 Rainforest distance (m) ** 55.97 Flower density (%) *** + 25.53 CV Flower density ns 24.68 260.40 Flower density (%) *** + 24.57 264.22 Flower density (%) *** + 24.86 CV Flower density 24.53 266.28 Rainforest distance (m) *** 24.77 275.43 Rainforest distance (m) *** 26.64 CV Flower density 24.77 276.03 CV Flower density ns 25.14 285.85

CV Bee species richness Rainforest distance (m) (*) + 1791.63 177.80 Rainforest distance (m) (*) + 1791.63 Flower density (%) ns 1749.25 179.61 Rainforest distance (m) (*) + 1791.63 CV Flower density ns 1775.06 179.93 Rainforest distance (m) ns 1791.63 Flower density (%) ns 1749.25 CV Flower density ns 1740.35 182.12 Flower density (%) ns 2011.26 CV Flower density ns 1983.19 182.62 Flower density (%) ns 2011.26 180.57 CV Flower density ns 2135.27 182.01

CV Bee abundance Flower density (%) * 1268.22 169.50 Rainforest distance (m) ns 1651.23 Flower density (%) ** 1179.54 170.15 Flower density (%) * 1268.22 CV Flower density ns 1215.53 170.88 Rainforest distance (m) ns 1651.23 Flower density (%) * 1179.54 CV Flower density ns 1170.42 172.59 CV Flower density ns 1605.96 175.17 Rainforest distance (m) ns 1651.23 175.84 Rainforest distance (m) ns 1651.23 CV Flower density ns 1605.25 177.55

Significance levels (*) < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001, n = 24. mean bee species richness per agro-forest increased with species richness and abundance per agro-forest observed at coffee increasing rainforest distance. The temporal variation in bee flowers (Table 3). The mean species richness of the transect surveys abundance was explained only by mean flower density and and of the coffee flower visitation per agro-forest were negatively decreased with increasing mean flower density per agro-forest related to increasing rainforest distance (Table 3). The temporal (Table 1). variation in bee species richness of the transect surveys (Fig. 2A) and the spatial variation in coffee flower-visiting bee species 3.3. Bee diversity and spatio-temporal stability of understory and richness per agro-forest were positively related to increasing coffee flower visitation surveys rainforest distance (Fig. 2B). The temporal variation in bee species richness of the transect Twenty-nine bee species with 2033 individuals foraged at surveys was negatively related to the mean of coffee flower- coffee flowers and 27 of them were also found in the understory of visiting species richness per agro-forest. The mean of coffee flower- the transect surveys outside coffee blooming (Table 2). Two visiting species richness per agro-forest was negatively related to Halictidae (sweat bee) species were found during coffee flower the spatial variation in flower-visiting bee species richness per visitation only and were not detected outside the coffee blooming agro-forest. The increasing spatial variation in flower-visiting bee during the transect surveys (Table 2). species richness significantly decreased the bee-pollinated fruit set The mean species richness and abundance per agro-forest of the (Fig. 2C) and increased the spatial variation of the bee-pollinated understory transect surveys were highly related to the mean fruit set among coffee plants per agro-forest (Fig. 2D). 1842 A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845

Fig. 2. (A) Relationship of the temporal variation (CV) in mean bee species richness per agro-forest of the understory transect surveys and rainforest distance (simple regressions: P = 0.0407, F = 4.73, R2 = 17.69%, n = 24). (B) Relationship of the spatial variation (CV) in mean bee species richness at coffee flowers per agro-forest and rainforest distance (simple regressions: P = 0.0125, F = 7.40, R2 = 25.16%, n = 24). (c) Relationship of mean bee-pollinated fruit set and the spatial variation (CV) in bee species richness at coffee flowers per agro-forest (simple regressions: P = 0.0244, F = 5.84, R2 = 20.99%, n = 24). (D) Relationship of the spatial variation (CV) in fruit set and the spatial variation (CV) in bee species richness at coffee flowers per agro-forest (simple regressions: P = 0.0495, F = 4.32, R2 = 16.42%, n =24).

4. Discussion 2004). The higher shared number of bee species over time in agro- forests near rainforests than in agro-forests isolated from rain- 4.1. Rainforest isolation and temporal provisioning of flower forests may be further explained by the agricultural matrix and resources management practices of the study area. The rainforest of the study area is a large continuous forest of a national park but the In order to manage and conserve wild crop pollinators, it is agricultural matrix is highly variable with small-scale and short- important to understand the relative influence of surrounding term changing management practices and scattered agro- natural habitats and flower resources on-farm sites for bee chemical use in all types of production systems. Although no community changes. Flower resources provided on sites are insecticides were applied in the studied agro-forests during the important to increase bee diversity (Ebeling et al., 2008)andthe time of the study (Klein et al., 2003), the surrounding agricultural changes in the temporal continuity of flower resources on site may fields were sprayed with various agro-chemicals that might have lead to changes in species identity over time as different pollinator influenced many bee species and lead to higher turnover of bee groups are attracted by different flower designs, forms, and species in samples of agro-forests apart from the rainforest. This densities (Thompson, 2001; Hegland and Boeke, 2006). Species idea is also promoted by the finding that the temporal variation in identity between temporally collected samples measured with the provisioning of flower resources inside the agro-forests itself the Jaccard index did not differ with flower density (Table 3), but has not affected the species similarity over time (no correlation was significantly higher in more isolated agro-forests. Flower and between the Jaccard index and the variation in flower density per nesting resources for bees are distributed over space and time in agro-forest, Table 3). Hence, the surrounding landscape matrix, and among distinct habitat types (Banaszak, 1992; Westrich, rather than the temporal variation in the provisioning of flower 1996). Hence, bee populations and species richness in agricultural resources on site, seems to be the driving factor for the temporal systems nearby natural habitats are depending on resource turnover of bee species and changes in species identity between distribution among habitats (Steffan-Dewenter et al., 2002; samples. The consequences of low species similarity over time in Kremen et al., 2007; Williams and Kremen, 2007). Even more, bee communities for pollination services will depend on the resources in the surrounding landscape can sometimes be more plant species involved and their pollination system and flower important for bee diversity and community structure than on- phenology. farm site resources (Holzschuh et al., 2008). Some bee species may In a study from California, Kremen et al. (2004) found a constant strongly depend on resources that are only available in natural high number of native bee species (excluding managed honeybee rainforests like cavity-nesting opportunities of tall or dead trees flower visits) over time in watermelon fields surrounded by high or nesting materials like resin of rainforest trees (Klein et al., proportion of semi-natural habitat in contrast to a higher variation A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845 1843

Table 2 Bee species list and overall abundance per species observed in 3600 min of transect surveys (= T) and in 1800 min of coffee flower-visitor observations (= C) in the 24 agro- forests. For single species, T- and P-values are given when mean abundance per agro-forest was related to rainforest distance (= Forest) or to mean flower density (= Flowers). Single species abundances were never significantly related to the temporal variation in flower density.

Bee species T C Forest Flowers

Amegilla sp. aff. samarensis (Ckll & Leveque, 1925) 58 20 2.62** Amegilla sp. zonata-group 58 2.57** Amegille whiteheadi (Ckll, 1910) 63 37 Apis cerana Fabr., 1973 246 269 7.62*** 5.59*** Apis dorsata binghami Ckll, 1906 298 229 6.65** 4.01*** Apis nigrocincta Sm., 1861 546 343 12.51*** – Ceratina (Ceratinidia) rugifrons Sm., 1879 63 26 Ceratina (Ceratinidia) cognata Sm., 1879 64 Ceratina (Ceratinidia) alexandrae Bkr, 2002 8 Ceratina (Ceratinidia) carinifrons Bkr, 2002 32 3.38*** Chalicodoma (Callomegachile) incisum (Sm., 1858) 26 6.03** Chalicodoma (Eumegachinana) tub. tuberculatum (Sm., 1857) 127 28 3.44*** Chalicodoma (Callomegachile) terminale (Sm., 1858) 12 5 9.92*** Coelioxys smithii D.T., 1896 23 5 2.66** 3.47*** Coelioxys (Allocoelioxys) sp. aff. confusa Sm., 1875 5 Coelioxys sp. 12 2.5* 2.4* Creightonella frontalis atrata Sm., 1853 57 101 2.78** Ctenoplectra elsei Bkr MS 7 Halictidae sp. 1 13 2.78** 3.35*** Halictidae sp. 2 22 2.13** Halictidae sp. 5 14 Halictidae sp. 8 16 Halictidae sp. 9 130 5.12*** Halictidae sp. 11 45 Halictidae sp. 12 34 Halictidae sp. 18 Halictidae sp. 21 72 Halictidae sp. 22 74 Heriades sp. 1 362 113 9.64*** 5.35*** Heriades sp. 2 62 47 Liptotriches sp. 16 67 Lipotriches sp. aff. ceratina Sm., 1857 92 3.24*** 4.79*** Megachile (Callochile) sp. aff. bakeri Ckll, 1919 61 17 Megachilidae (Eutricharaea) sp. 1 66 3.82*** Megachilidae (Eutricharaea) sp. 2 16 Nomada sp. 32 Nomia (Thoraconomia) thoracica Sm., 1875 83 105 Nomia (Curvinomia) fulvata (F., 1804) 72 Nomia (Hoplonomia) hoplomachus Bkr, 2002 8 Paracella sp. 1 18 21 Paracella sp. 2 58 10 2.92** Patellapis (Pachythalictus) sp. 1 117 15 Patellapis (Pachythalictus) sp. 2 4 Pithitis unimaculata (Sm.) 29 Thyreus nitidulus quartinae (Grib., 1884) 48 10 3.69*** Thyreus castalius Lieft. 15 Torridapis ducalis flavipennis (Fr., 1908) 11 24 3.88*** 4.14*** Trigona (Lepidotrigona) terminata Sm., 1875 245 106 11.74*** Trigona (Heterotrigona) sp. 1 83 19 Trigona ssp. 180 154 3.69*** 7.22*** Trigona (Heterotrigona) sp. 2 85 23 7.83*** Xylocopa sp. 5 Xylocopa (Koptortosoma) aestuans (L., 1758) 142 33 2.63** Xylocopa (Zonohirsuta) dejeanii nigrocaerulea Sm., 1874 68 53 Xylocopa (Koptortosoma) smithii Rits.,1876 14 12 7.18*** n = 24. * P < 0.05. ** P < 0.01. *** P < 0.001. in bee species richness in isolated agriculture. The results the same as discussed above in respect to changes in species presented here are in accordance with the finding in California similarity and may be mainly caused by the high spatial and with the mean species numbers of the understory and coffee temporal variability in management practices of the agricultural flower-visiting surveys decreasing, but with increasing temporal landscape. and spatial variation in the coffee flower-visiting species richness, Although bee species richness is high near rainforest, it can not with increasing rainforest isolation. The reasons for declining bee necessarily assumed to be highest in the interior of the rainforest species richness with isolation from natural habitat is already and although bee community composition changed from the forest frequently discussed and reviewed by Ricketts et al. (2008). The interior to tropical countryside, overall bee diversity is sometimes reasons for the higher spatio-temporal variation in bee species not changing or is even lower in forest interiors (Klein et al., 2002; richness in agricultural fields isolated from natural habitat may be Brosi et al., 2008). During the transect surveys, an additional 1844 A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845

Table 3 Correlation matrix represented by Pearson Correlation Coefficient values and P-values between the habitat variables rainforest distance (m), mean flower density (%), and temporal variation in flower density with bee community variables of the understory transect surveys and the coffee flower-visiting surveys and bee-pollinated coffee fruit set.

Forest Flower CV(t) Richness Abundance CV(t) CV (t) Jaccard Richness Abundance CV(s) CV(s) Bee distance# densityy Flower transecty transecty Richness Abundance coffee coffee Richness Abundance pollination densityy transect transect coffee coffeey

Flower densityy 0.29———— —— ——— —— — CV(t) Flower densityy 0.46* 0.09 — — — — — — — — — — — Richness transecty 0.60** 0.52** 0.27 — — — — — — — — — — Abundance transecty 0.57** 0.72*** 0.07 0.88*** — —— ——— —— — CV(t) Richness transect 0.42* 0.39 0.11 0.49* 0.49* ———————— CV(t) Abundance transect 0.06 0.61** 0.18 0.40(*) 0.40(*) 0.37(*)——————— Jaccard 0.35(*) 0.24 0.17 0.31 0.31 0.22 0.27 — — — — — — Richness coffee# 0.70*** 0.45* 0.21 0.88*** 0.88*** 0.44* 0.26 0.30 — — — — — Abundance coffee# 0.09 0.34 0.17 0.65*** 0.65** 0.21 0.42* 0.26 0.54** ———— CV(s) Richness coffee 0.50* 0.41* 0.41 0.57** 0.56*** 0.14 0.18 0.55** 0.47* 0.47* — — — CV(s) Abundance coffeey 0.41* 0.29 0.31 0.54** 0.54** 0.19 0.03 0.37(*) 0.50* 0.54** 0.47* —— Bee pollination 0.36(*) 0.39(*) 0.04 0.80*** 0.81*** 0.26 0.32 0.34 0.69*** 0.58** 0.46* 0.46* — CV(s) Bee pollination 0.36(*) 0.17 0.14 0.51* 0.51* 0.16 0.13 0.56** 0.50* 0.25 0.41* 0.40* 0.51*

Following variables of the transect survey were tested: mean bee species richness and abundance, mean Jaccard index, temporal variation in bee species richness and abundance. Following variables of the coffee flower-visiting surveys and coffee pollination were tested: mean bee species richness and abundance, spatial variation in bee species richness and abundance and bee-pollinated fruit set and spatial variation in bee-pollinated fruit set. Variations are calculated by the CV, and CV(t) represents temporal variation of the transect surveys at different sampling days per agro-forest and CV(s) spatial variation of the flower visits at different coffee plants per agro-forest. Significances *P < 0.05; ** P < 0.01; *** P < 0.001; n = 24 study sites. # Square-root transformed. y Log-transformed.

transect was established at 1 km from the forest margin into the indicating why diversity can be essential for reaching high seed set rainforest interior. The additional data were not included in the in crop production (Hoehn et al., 2008). analyses because samples were just taken from one transect This study focused at only four (bee pollination) and three location in the forest interior and replicates are missing. Never- (flower-visiting bee species richness) replicated coffee plants per theless, it should be mentioned that mean bee species richness and agro-forest respectively to analyze the spatial variation of the temporal variation in species richness was lower in the forest response variables. For the short bloom of coffee increasing the interior plot than in the agro-forests located near the forest margin number of replicates could not be handled. Future studies may and small ground-nesting bees could not be found in the rainforest increase the number of plant replicates per site by using shorter interior. observation times per plant. Further, different plant parts can be noted and observed as well as different locations per site like edge 4.2. Spatio-temporal stability in bee species richness and versus interior. Such sampling efforts will increase the overall consequences for forest-based pollination services variation among samples per site, which may accentuate overall patterns. It is also important to focus at different plant systems in The increasing spatial variation in bee species richness with different landscape settings to conclude about the persistency of increasing rainforest isolation not only increases the bee- the relationships between landscape variables, bee diversity, and pollinated coffee fruit set, but also decreases the variation in spatial variation in bee pollination. The relationship of bee bee-pollinated coffee fruit set. High bee diversity is known to diversity and spatial pollination stability according to this study stabilize pollination services among sampling days and between seems to be reflected by the changes in bee diversity in space and years (Kremen et al., 2004; Ricketts, 2004; Winfree and Kremen, time. As the results may be strongly related to the high variability 2008) and although the effects of diversity on ecosystem stability in management practices in the surrounding landscape, experi- are frequently discussed, these studies mainly address the effects mental manipulations of bee diversity under controled conditions of temporal variation. In contrast, spatial variation of samples is are further needed to understand the importance of spatial and rarely analyzed (Weigelt et al., 2008). As bee species richness is temporal variability in bee communities for pollination. known to be important for high coffee pollination (e.g. Klein et al., In conclusion, crops grown near intact rainforests and which 2003), it is not surprising that reduced spatial variation in bee profit from the pollination by many species may fluctuate less in species richness decreased the spatial variation in bee pollination. bee-pollinated fruit set across plants than crop plants in isolated This means in the high bee diversity agro-forests near the agriculture that receive low or even single species pollination rainforest, all coffee plants were visited by many bee species services. The underlying mechanisms seem to be driven by spatial and bee-pollinated fruit set was equally high for the plants, and temporal bee community changes. These findings, besides the whereas the low bee diversity agro-forests were visited by variable economic value of crop pollination (Gallai et al., 2008), the numbers of bee species and bee-pollinated fruit set was variable abandonment of beekeeping in regions affected by ‘‘Africaniza- among coffee plants. This additional aspect underlines the tion’’ of honey bees (Brosi et al., 2007), and the trend of agriculture importance of high bee diversity for pollination. Mechanisms favouring the cultivation of pollinator-dependent crops (Aizen behind the diversity-pollination relationship are recently dis- et al., 2008), accentuates the importance to focus on bee habitat cussed (Klein et al., 2008, in press) and detailed observations and resource connection in agricultural matrixes to promote high demonstrate that partitioning of flower resources in space (flower and less variable bee diversity for forest-based pollination height) and time (time of the day) are important mechanisms services. A.-M. Klein / Forest Ecology and Management 258 (2009) 1838–1845 1845

Acknowledgements Klein, A.M., Steffan-Dewenter, I., Tscharntke, T., 2003. Fruit set of highland coffee increases with the diversity of pollinating bees. The Proceedings of the Royal Society of London, Series B 270, 955–961. Many thanks to all members, and especially the speaker T. Klein, A.M., Steffan-Dewenter, I., Tscharntke, T., 2004. Foraging trip duration and Tscharntke, of the German-Indonesian Research Project STORMA density of megachilid bees, eumenid wasps and pompilid wasps in tropical agroforestry systems. Journal of Ecology 73, 517–525. (Stability of Tropical Rainforest Margins) for the support and Klein, A.M., Steffan-Dewenter, I., Tscharntke, T., 2006. Rainforest promotes trophic coordination of field work, M.R. Guariguata, one anonymous interactions and diversity of trap-nesting hymenoptera in tropical agroforestry. referee, and S. Hendrix for helpful comments on the mansucript. Journal of Animal Ecology 75, 315–323. D.B. Baker is greatly acknowledged for bee identification. E. Klein, A.M., Vaissie`re, B.E., Cane, J.H., Steffan-Dewenter, I., Cunningham, S.A., Kre- men, C., Tscharntke, T., 2007. Importance of pollinators in changing landscapes Tamalagi, S.A. Kaisang, and S.D.G. Massiri for field assistance; many for world crops. Proceedings of the Royal Society of London, B 274, 303–313. Indonesian smallholders for research permission and helpful Klein, A.M., Cunningham, S.A., Bos, M., Steffan-Dewenter, I., 2008. Advances in information. This research was funded by the German Academic pollination ecology from tropical plantation crops. Ecology 89, 935–943. Klein, A.M., Mueller, C.M., Hoehn, P., Kremen, C. 2009. Understanding the role of Exchange Program, the German Science Foundation, and the species richness for crop pollination services. In: Bunker, D., Hector, A., Loreau, Alexander von Humboldt foundation. M., Naeem, S. (Eds.), Biodiversity, ecosystem functioning, and human wellbeing. An ecological and economic perspective. Oxford University Press, (in press). Kremen, C., Williams, N.M., Bugg, R.L., Fay, J.P., Thorp, R.W., 2004. The area Appendix A. Supplementary data requirements of an ecosystem service: crop pollination by native bee commu- nities in California. Ecology Letters 7, 1109–1119. Kremen, C., Williams, N.M., Aizen, M.A., Gemmill-Herren, B., LeBuhn, G., Minckley, Supplementary data associated with this article can be found, in R., Packer, L., Potts, S.G., Roulston, T., Steffan-Dewenter, I., Va´zquez, D.P., Win- the online version, at doi:10.1016/j.foreco.2009.05.005. free, R., Adams, L., Crone, E.E., Greenleaf, S.S., Keitt, T.H., Klein, A.M., Regetz, J., Ricketts, T.H., 2007. Pollination and other ecosystem services produced by mobile organisms: a conceptual framework for the effects of land-use change. References Ecology Letters 10, 299–314. R Development Core Team. 2009. R: A language and environment for statistical Aizen, M.A., Garibaldi, L.A., Cunningham, S.A., Klein, A.M., 2008. Long-term global computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3- trends in crop yield and production reveal no current pollination shortage but 900051-07-0, URL http://www.R-project.org. increasing pollinator dependency. Current Biology 18, 1–4. Ricketts, T.H., 2004. Tropical forest fragments enhance pollinator activity in nearby Banaszak, J., 1992. Strategy for conservation of wild bees in an agricultural land- coffee crops. Conservation Biology 18, 1262–1271. scape. Agriculture, Ecosystem and Environment 40, 179–192. Ricketts, T.H., Regetz, J., Steffan-Dewenter, I., Cunningham, S.A., Kremen, C., Brosi, B.B., Daily, G.C., Ehrlich, P.R., 2007. Bee community shifts with landscape Bogdanski, A., Gemmill-Herren, B., Greenleaf, S.S., Klein, A.M., Mayfield, context in a tropical countryside. Ecological Applications 17, 418–430. M.M., Morandin, L.A., Ochieng, A., Viana, B.F., 2008. Landscape effects on Brosi, B.B., Daily, G.C., Shih, T.M., Oviedo, F., Dura´n, G., 2008. The effects of forest crop pollination services: are there general patterns? Ecology Letters 11, fragmentation on bee communities in tropical countryside. Journal of Applied 499–515. Ecology 45, 773–783. Roubik, D.W., 1988. Ecology and natural history of tropical bees. Cambridge Uni- Brown, J.C., Albrecht, C., 2001. The effect of tropical deforestation on stingless bees veristy Press, Cambridge. of the genus Melipona (Insecta: Hymenoptera: Apidae: Meliponini) in central Roubik, D.W. 1995. Pollination of cultivated plants in the tropics. FAO Agricultural Rondonia, Brazil. Journal of Biogeography 28, 623–634. Services Bulletin 118, Rome. Burnham, K.P., Anderson, D.R., 2002. Model selection and mutimodel inference. A Sala, O.E., Chapin III, F.S., Armesto, J.J., Berlow, R., Bloomfield, J., Dirzo, R., Huber- practical information - theoretic approach. Second edition. Springer Science and Sanwald, E., Huenneke, L.F., Jackson, R.B., Kinzig, A., Leemans, R., Lodge, D., Business Media, LLC, New York, p. 66. Mooney, H.A., Oesterheld, M., Poff, N.F., Sykes, M.T., Walker, B.H., Walker, M., Chao, A., Chazdon, R.L., Colwell, R.K., Shen, T.J., 2005. A new statistical approach for Wall, D.H., 2000. Global biodiversity scenarios for the year 2100. Science 287, assessing compositional similarity based on incidence and abundance data. 1770–1774. Ecology Letters 8, 148–159. Shuler, R.E., Roulston, T.H., Farris, G.E., 2005. Farming practices influence wild Colwell, R.K. 2006. EstimateS: Statistical estimation of species richness and shared pollinator populations on squash and pumpkin. Journal of Economic Entomol- species from samples. Version 8.0 for windows. User’s Guide and application ogy 98, 790–795. published at: http://viceroy.eeb.uconn.edu/EstimateS. Slaa, J.E., Sa´nchez, L.A., Malagodi-Braga, K.S., Hofstede, F.E., 2006. Stingless bees in Ebeling, A., Klein, A.M., Schumacher, J., Weisser, W., Tscharntke, T., 2008. How does applied pollination: practice and perspectives. Apidologie 37, 293–315. plant richness affect structure and stability of pollinator communities? Oikos Steffan-Dewenter, I., Mu¨ nzenberg, U., Bu¨ rger, C., Thies, C., Tscharntke, T., 2002. 117, 1808–1815. Scale-dependent effects of landscape context on three pollinator guilds. Ecology Gallai, N., Salles, J.M., Settele, J., Vaissie`re, B.E., 2008. Economic valuation of the 83, 1421–1432. vulnerability of world agriculture confronted with pollinator decline. Ecological Thompson, J.D., 2001. How do visitation patterns vary among pollinators in relation Economics, doi:10.1016/j.ecolecon.2008.06.014. to floral display and floral design in a generalist pollination system? Oecologia Griffin, J., O’ Gorman, E., Emmerson, M., Jenkins, S., Klein, A.M., Loreau, M., Symstad, 126, 386–394. A. 2009. Biodiversity and stability of ecosystem functioning. In: Bunker, D., Tylianakis, J.M., Rand, T.A., Kahmen, A., Klein, A.M., Buchmann, N., Perner, J., Hector, A., Loreau, M., Naeem, S. (Eds.), Biodiversity, ecosystem functioning, and Tscharntke, T., 2008. Resource heterogeneity moderated the biodiveristy-func- human wellbeing. An ecological and economic perspective. Oxford University tion relationship in real world ecosystems. PlosBiology 6, e122. Press, (in press). Vergara, C.H., Badano, E.I., 2008. Pollinator diversity increases fruit production in Heard, T., 1999. The role of stingless bees in crop pollination. Annual Review of Mexican coffee plantations: The importance of rustic management systems. Entomology 44, 183–206. Agriculture, Ecosystems and Environment 129, 117–123. Hegland, S.J., Boeke, L., 2006. Relationships between the density and diversity of Weigelt, A., Schumacher, J., Roscher, C., Schmid, B., 2008. Does biodiversity floral resources and flower visitor activity in a temperate grassland community. increase spatial stability in plant community biomass? Ecology Letters 11, Ecological Entomology 31, 532–538. 338–347. Herrmann, F., Westphal, C., Moritz, R.F.A., Steffan-Dewenter, I., 2007. Genetic Westphal, C., Steffan-Dewenter, I., Tscharntke, T., 2003. Mass-flowering crops diversity and mass resources promote colony size and forager densities of a enhance pollinator densities at a landscape scale. Ecology Letters 6, 961– social bee (Bombus pascuorum) in agricultural landscapes. Molecular Ecology 965. 16, 1167–1178. Westrich, P., 1996. Habitat requirements of central European bees and the problems Hoehn, P., Tscharntke, T., Tylianakis, J.M., Steffan-Dewenter, I., 2008. Functional of partial habitats. In: Matheson, A., Buchmann, S.L. (Eds.), Westrich, R., Wil- group diversity of bee pollinators increases crop yield. Proceedings of the Royal liams, I.H. (Eds.), The conservation of bees. Academic Press, London, pp. 1–16. Society of London, Series B 275, 2283–2291. Williams, N.M., Kremen, C., 2007. Resource distributions among habitats determine Holzschuh, A., Steffan-Dewenter, I., Tscharntke, T., 2008. Agricultural landscapes solitary bee offspring production in a mosaic landscape. Ecological Applications with organic crops support higher pollinator diversity. Oikos 117, 354–361. 17, 910–921. Klein, A.M., Steffan-Dewenter, I., Buchori, D., Tscharntke, T., 2002. Effects of land-use Winfree, R., Kremen, C., 2008. Are ecosystem services stabilized by differences intensity in tropical agroforestry systems on flower-visiting and trap-nesting among species? A test using crop pollination.. Proceedings of the Royal Society bees and wasps. Conservation Biology 11, 683–693. of London, Series B. 276, 229–237.