Bees are capable of passing through a variety of landscape structures, and bumble bees, while generally exhibiting high site fidelity, have been found to cross both natural and artificial barriers with little difficulty. Therefore, it is likely that anthropogenic land use change is not a barrier to movement. As agricultural and urban areas continue to be the largest and fasting growing forms of land use conversion, it is critical to understand the impacts of these landscape-scale changes on species distributions in order to predict and plan for ecological impacts as global change continues. Relationships between community metrics and land use change alone to do not reveal the complex interplay of land use change and seasonality. Variability in patterns due to seasonality has not been taken into account in many pollinator studies in anthropogenic landscapes, despite the known clear linkage between pollinators and floral resources. Bringing attention to how anthropogenic landscapes experience different temporal dynamics is relevant to the numerous conservation and restoration projects being done in anthropogenic landscapes. There are many similarities between urban and agricultural landscapes, and projects being conducted within them to attract pollinators could benefit from a crossover understanding of the impacts of anthropogenic land use change. In addition to contributing to a better understanding of how change in landscape use, particularly urbanization, affects bee community population dynamics, this study illustrates the importance of observing temporal dynamics in urban ecology studies.Increasing temperatures as a result of global climate change have led to shifts in phenology for many species, drainage collection pot and widespread debate over the consequences of critical interaction mismatches. However, not all phenological change is the direct result of changing climate.
Land use change, such as urbanization and agricultural expansion, includes the deliberate introduction of novel plants into communities. These plants, both exotic ornamentals and crops, are often accompanied by watering and supplemental nutrient inputs that extend survival potential in the targeted landscape, leading to different flowering seasons. Therefore, on a plant community-scale, different land use types can be expected to experience distinct patterns of phenological change. Land surface phenology is the timing of overall surface vegetation growth, and differs from traditional definitions of vegetation phenology , which are being used to product 250-m spatial resolution products every 16 days . In some cases, the changes in land surface phenologies between years have given insight into the history of regions that have experienced socio-economic and geopolitical transitions, such as changes in irrigation regimes in central Asia after the fall of the Soviet Union, or the expansion of urbanization in parts of Mexico. Differences in phenology between neighboring land use types within a year also provide insights, such as vegetation phenology of urban landscapes found to be out of synchrony with patterns of phenology in the surrounding desert. As a result of land use change, such phenological differences in vegetation could lead to phenological differences in other groups of organisms, especially if plants exert bottom-up control on the organisms that interact with them. Primary productivity can be linked to biodiversity. Therefore, there exists great potential to use remote sensing of primary productivity data as a way to predict biodiversity. However, early efforts to apply this technique were less powerful than expected.
Some evidence suggests that remote sensing data can predict biodiversity; for example, peak vegetation indices in multiple studies are correlated with higher avian diversity, although in other systems the relationship is less clear. Linking remote sensing data with biodiversity has been limited despite its great potential. Part of the problem may be that, in many comparisons, vegetation indices are treated statically, rather than as temporally dynamic. Use of a multi-season within year vegetation index was found to be a much more accurate predictor of biodiversity. Additionally, these indices may be more able to uncover patterns across landscape types with more dramatic differences in vegetation, such as human-altered landscapes. Also, biodiversity may be too broad, and instead, we should focus on those organisms that exhibit tight linkages with plant communities. In this paper we focus on bees, a key pollinator group with close vegetation associations, since bees strongly depend on flowers for both nectar and pollen. Bees provide the majority of animal-mediated pollination services on which an estimated 87.5% of flowering plants depend. The value of pollination in agriculture is estimated at $200 billion worldwide , due to many foods that are essential for food security and a healthy human diet, including numerous fruits, vegetables, and nuts that require bee pollination. Bees are closely linked to floral availability in their environment. However, the temporal dynamics of floral resources can vary between land use types. In California grasslands, there is typically a large burst of blooming in the spring, which tapers off in the summer. Urban areas often have ornamentals enhanced with external inputs that results in a steady patterns with only minor changes throughout the year, while agricultural landscapes have booms and busts of flowering that follow the pattern of local crops.
For this project, we explore how vegetation phenology varies in a human-altered California grassland landscape, and whether or not these changes in phenology correlate with those of the bee community that depends on floral resources. Specifically, we ask: 1) Do humanaltered landscapes in California grasslands experience phenological diversity that is out of synchrony with surrounding natural areas and 2) Do these spatio-temporal patterns correlate with bee distribution data?The bee community was sampled at multiple time points from 2010-2012. Within this region, sites were selected to be at least 1 km away from all others, based on maximum assumed bee foraging ranges. Although certain bee species have been recorded foraging as far as 1400 m, most bees have nesting and foraging habitat within a few hundred meters of each other. At each site we laid out a standardized pan trapping transect of fifteen 12 ounce bowls spaced 5 meters apart in alternating colors of fluorescent blue, white, and yellow. Bowls were filled to the brim with soapy water . In 2010, transects were set up for a 4 hour period between 10:30am to 2:30pm , with 4 sites sampled per day, and all sites sampled on consecutive days. These 2010 transects were run twice, once in the early summer, and once in the late summer. In 2011 and 2012, sampling was altered for transects to be set up for a 24 hour period, so that more sites could be run simultaneously and collections made more often. All 24 sites were sampled within two consecutive collecting windows of 24 hours, and were run four times each year: early spring, late spring, early summer, and late summer. The goal of collection was to sample the bee community that was flying through the site searching for resources. Because we were interested in landscape-level effects, we tried to control local variables as much as possible. All sites were selected in easily accessible, open areas that received full sun. Natural areas were in grassland habitat, so we selected agricultural sites that were either weedy field margin edges or fallow fields, square plastic pot and urban sites that were vacant lots or green ways. The human-altered sites were deliberately selected to not be adjacent to any mass-flowering crops or gardens. Bees were collected from the pan traps by using a metal strainer, rinsed with water, frozen overnight or longer, and then pinned and labeled. Specimens were sorted to the genus level, and then to the species level with the assistance of Dr. Robbin Thorp . The only exception to identification at the species level were bees of the genus Lasioglossum, due to their overwhelming abundance, limited availability of taxonomic expertise for this group, and lack of known ecological diversity. Voucher specimens and the majority of the total collection will be deposited at the Essig Museum of Entomology at UC Berkeley.For most models of total bee abundance, there was a significant impact of land use type, vegetation index value, and an interaction between the two . AIC values decreased, indicating better model fit, as the time lag of vegetation data increased to 48 days prior to the collecting event. Similar patterns were not found for species richness, and there was little to no relationship betweeen vegetation indices and species richness. In general the relationship between higher vegetation indices and higher bee abundance was positive. However, a time lag of 16 days between the remote sensing data and the closest sampling date of bee collection exhibited differences in patterns between land use types. For natural areas, there appeared to be a positive correlation slope between EVI and higher bee abundance.
The slope for bee abundance in urban sites was close to zero, and was a negative slope in agricultural sites . No other scenarios of land use type, bee abundance, and vegetation index was significantly negative. Urban sites had a high amount of overlap between seasons in the correlations between vegetation indices and total abundance. Agricultural sites also had overlap between seasons, but overall variation was higher than with urban sites. Natural sites had little overlap between months and correlations were more dispersed, particularly for early and late spring .This study demonstrates the role of land use change in leading to shifts in phenology, a result often attributed to climate change. We found major differences in land surface phenology and bee community spatio-temporal distributions between urban, agricultural, and natural land use types. The phenology of land surface vegetation human-altered landscapes are is of synchrony with surrounding California grassland natural areas. In addition to different patterns of phenological change, different land use types exhibit variability in the ranges and standard deviations of their land surface vegetation phenology. Further, these patterns correlate with spatio-temporal bee distribution data. In California grasslands, floral availability is largely driven by temperature and rainfall, resulting in a large burst of blooms in the spring, and by the end of the summer, there are few floral resources available. However, in human-altered landscapes, landscaping and water irrigation patterns are likely even stronger influences. Vegetation in urban areas is highly diverse, and selected for aesthetic and convenience reasons. Urban areas, while having less green space, often have many exotic ornamental plants which are supplemented with water and nutrient inputs that allow for an extended flowering season. As a result, urban areas are characterized by low, but constant, floral resources throughout the year. Agricultural areas have large patches of dense, often homogenous, floral resources that will fluctuate greatly from early spring to the end of the summer. In our system, stone fruit orchards are in flower in the spring, but throughout the summer there are other crops in flower such as alfalfa, tomato, corn, and bell peppers. This asynchrony in land surface phenology between neighboring land use types is similar to what Buyantuyev and Wu found in the desert landscapes of the southwestern United States. They found the timing of highest peaks of vegetation indices to be different between land use types, which they attributed to a decoupling in the urban sites from the local climatic drivers. It is likely that a similar scenario occurs in California, with grasslands juxtaposed against urban and agricultural areas that have different vegetation types and additional inputs. Beyond the different timing in vegetation indices, it is important to note the significantly different standard deviation and ranges of pixels of the same land-use type. Natural land use types were quite similar to one another given their relatively small standard deviations and ranges over time. However, in the human-altered landscapes, particularly agricultural, there was much higher variation. In other words, even though natural areas can be considered patchy, they are not nearly as patchy as urban and agricultural areas. One reason for the enhanced patchiness is that in urban and agricultural landscapes, there are many different land owners and management decisions being made on a relatively micro-scale, resulting in a wide diversity of vegetation types being selectively planted and cared for in different ways across the landscape. Instead of vegetation type shifting on the scale of a few kilometers, it might actually differ on the scale of a few meters. Such extreme patchiness of vegetation can have many implications for organisms dependent on floral resources. Additionally, varying patterns in vegetation in urban landscapes have been found to be closely tied to socio-economic factors, suggesting an important factor to consider when exploring biodiversity in human-altered landscapes.