DOI: 10.5061/dryad.bg79cnphc
title: Landscape structure and farming management interacts to modulate pollination supply and crop production in blueberries

description: Pollination services are affected by landscape context, farming
 management, and pollinator community structure, all of which impact flower
 visitation rates, pollen deposition and final production. We studied these
 processes in Argentina for Highbush Blueberry crops which depend on
 pollinators to produce marketable yields.  We studied how land
 cover and honeybee stocking influence the abundance of wild and managed
 pollinators in blueberry crops, using structural equation modeling to
 disentangle the cascading effects through which pollinators contribute to
 blueberry fruit number, size, nutritional content and overall
 yield.  All pollinator functional groups responded to landscape
 changes at a spatial scale under 1000 m, and the significance or direction
 of the effects were modulated by the field-level deployment of honeybee
 hives.  Fruit diameter increased with pollen deposited, but
 decreased with honeybee abundance, which, had indirect effects on fruit
 acidity and sugar content. Honeybees had a positive effect on the number
 of fruit produced by the plants and also benefited the overall yield (kg
 plant-1) through independent effects on both the quality and quantity
 components of fruit production. Synthesis and applications: Deployment of
 beehives in blueberry fields can buffer, but not compensate for the
 negative effects on honeybee abundance produced by surrounding large scale
 none-flowering crops. Such compensation would require high-quality
 beehives by monitoring their health and strength. The contribution of
 honeybees to crop production is not equal across production metrics. That
 is, higher abundance of honeybees increases the number of berries
 produced, but at the cost of smaller and more acidic fruits, potentially
 reducing market value. Growers must consider this trade-off between fruit
 quantity and quality when actively managing honeybee abundance.
description: <em>Sampling design and
 pollinator observation: </em>
 In total we sampled pollinators on nine farms, eight in
 2020 and six in 2021 —five of these farms were sampled in both years.
 Five farms had honeybee hives to enhance crop pollination while four rely
 on wild pollinators or feral honeybees (Appendix 1 Figure
 S1a). On each farm, we
 established an edge area (25 m from the field margin) and an inner area
 (50 m from the field margin), each comprising two 70 m transects running
 parallel to the field margin and separated by eight meters. On each of the
 four transects we selected 25 plants in full flower on which we conducted
 three 30-second pollinator counts, one in the morning, one at midday, and
 one in the afternoon. All sampling took place between 10:00 and 17:00 on
 sunny days with low wind and a temperature above 15 °C. We recorded the
 abundance of honeybees, small wild bees —any bee smaller than a honeybee —
 hoverflies (<em>Syrphidae</em>), and butterflies. Hummingbirds
 and large wild bees (bumblebees
 <em>Bombus</em> spp. and carpenter bees <em>Xylocopa</em>
 spp., which are all larger
 than honeybees) showed behaviors that made them difficult to record as
 they fled when surveyors approached the plants. Therefore, after every 25
 plant pollinator counts, we walked the same transect to record the
 abundance of hummingbirds and large wild bees for five minutes. This
 sampling protocol was repeated twice for each farm in each year (2020= 56
 hours, 2021= 42 hours of pollinator counts).
 <em>Landscape
 classification:</em> All land use classifications were carried out
 using the interactive Google Earth Engine application ‘Your Maps Your Way’
 (YMYW) (Morton & Schmucki, 2023). A detailed explanation of the classification
 process can be found in Appendix 1, Table S1. In summary, we classified
 the different land covers into three broad categories: (i) natural cover
 (natural primary forest, secondary forest, and shrubland), (ii) flowering
 crops (citrus and blueberry), and (iii) large-scale crops (sugarcane and
 soybean crops). We grouped flowering crops together because blueberries
 occupy a small area compared to citrus, although both are perennial and
 provide comparable resources (Emerald bloom in August and citrus in
 September). We used the <em>terra</em> (Hijmans 2022) and <em>sf</em> (<em>Pebesma</em>, 2018) R packages to define the area of the three land use classes within concentric circles with a radius of 200 to 4000 m around each site, progressively increasing the radius by 200 m (Appendix 1 Figure S1a). This was done to identify the spatial scale of pollinator responses to land use. <em>Cascading effects: from pollinators to production </em> <em>Pollinator counts:</em> During the 2021 flowering season (July – August), we used a subset of the nine farms (N = 3) to examine the effects of pollinators on blueberry pollen deposition and productivity metrics. On these farms growers manage pollination services using honeybee hives. On each farm, we selected five to six plots (Emerald cultivar, plot size 1.31 ± 0.09 ha) distributed from the edge of the farm to the interior to capture the potential variation in underlying pollination services, soil condition, irrigation system and plant age (Appendix 1 Figure S1b). The average distance between plots was 384.4 ± 197.5 m. In each plot we randomly selected five plants and conducted a 5-minute pollinator count per plant under the same weather conditions as mentioned above (26.6 ± 2.8 plants per farm). Previously, we estimated the floral display size per plant by combining the flowering percentage of the plant, the total fruits produced (see <em>production metrics</em> section) and the fruit set of the Emerald cultivar at each farm (see the detailed procedure in Appendix 1 Table S3). We recordedthe abundance of honeybees and small wild pollinators. We also used the plant as a central point to record the abundance of hummingbirds and large wild bees in an area of 12 m<sup>2</sup> (area occupied by 14 blueberry plants). The density of honeybee hives within 200 m (12.5 ha) of each sampled plot was recorded (Appendix 1 Figure S1b). Each plant was sampled twice during the ~30 day flowering period (13.3 hours of pollinator observation). <em>Pollen deposition:</em> After flower anthesis, we collected three styles per plant from senescent flowers (Ntotal = 240). These were placed on a microscope slide after a transversal cut of the style at the stigma height and stained with Alexander’s solution (Alexander, 1969). We then counted the number of pollen grains as a measure of the stigmatic pollen load. <em>Production metrics:</em>  We considered the following metrics to assess the quality and quantity of blueberry production: 1) We visited each sampled plant and counted the total number of fruits on two randomly selected primary branches. The product of the average number of fruits per primary branch and the number of primary branches was used as an estimate of the total number of fruits per plant; 2) We randomly selected ten mature fruits per sampled plant and measured their equatorial diameter; 3) Plant yield (kg plant<sup>-1</sup>) was the product of average fruit weight (Nfruits per plant = 10) and the total number of fruit produced; 4-7) Nutritional content based on a 30g fruit sample in the form of degrees Brix (measure of sugar content), total acidity, and concentration of anthocyanins (Appendix 1 in Table S4 for the laboratory protocol).
description: # From landscape and pollinators to crop productivity: the step-by-step of
 pollination service in blueberry crops
 [https://doi.org/10.5061/dryad.bg79cnphc](https://doi.org/10.5061/dryad.bg79cnphc) **Data description** Data sets and R code files employed to analyze the cascading processes involving landscape, farming management, pollinators, and pollen deposition, affecting several dimensions of blueberry production. **Files** 1\. pollinators\.xlsx — Excel file holding data small \(sheet 2\) and large pollinators \(sheet 3\) for landscape analysis\. The sheet 1 describes all columns in sheets 2 and 3\. NA = not available / missing value\. 2\. land\_cover\_predictors\.csv — Land cover predictors\. This data set contains 13 columns, and each row corresponds to a different spatial scale by farm\. Columns description: * Name: name of the farm where the data was collected. * ORIG\_FID: identifier. * arandano: blueberry (number of pixels, each of 9m<sup>2</sup> resolution). * arbustal: shrub land (number of pixels, each of 9m<sup>2</sup> resolution). * bosque\_alto: high mountain forest (number of pixels, each of 9m<sup>2</sup> resolution). * bosque\_pedemonte: primary mountain forest (number of pixels, each of 9m<sup>2</sup> resolution). * bosque\_secundario: secondary forest (number of pixels, each of 9m<sup>2</sup> resolution). * citrus: citrus crops (number of pixels, each of 9m<sup>2</sup> resolution). * distance: spatial scale (from 200 m to 4000 m). * rio: rivers (number of pixels, each of 9m<sup>2</sup> resolution). * soja: soybean (number of pixels, each of 9m<sup>2</sup> resolution). * urbano: urban area (number of pixels, each of 9m<sup>2</sup> resolution). * zafra: sugar cane crops (number of pixels, each of 9m<sup>2</sup> resolution). 2\. SEM\_data\.txt — dataset for conducting structural equation modeling \(SEM\) analysis\. Each row denotes an observation per plant\. Columns description: * farm: name of the farm where the data was collected. * plot: plot within the farm. * apis: honeybee abundance (averaged over two sampling counts). * dens\_200: honeybee beehive density in a radius of 200 m. * flores\_disp: average floral display size per plant (number of flowers). * wild\_pol: small-wild pollinators abundance (averaged over two sampling counts). * bombus: large bees and hummingbird abundance (averaged over two sampling counts). * no\_polen: stigmatic pollen load (averaged per plant). * cv\_no\_polen: coefficient of variation of the stigmatic pollen load. * mean\_f\_diam: equatorial diameter (averaged per plant). * acidez: total acidity. * brix: degree brix (sugar content). * anton: anthocyanin concentration. * yield\_kg: plant yield (kilograms of fruits produced). * total\_fruits: total fruits produced per plant. 3\. landscape\_SEM\.R — R script for reproducing landscape and SEM analyses\. 4\. ramirez\_mejia\_etal\_results\.html — html file showing code and outputs of landscape