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Ongoing declines of bees and other pollinators are driven in part by the loss of critical floral resources and nesting substrates. Most conservation/restoration efforts for bees aim to enhance floral abundance and continuity but often assume the same actions will bolster nesting opportunities. Recent research suggests that habitat plantings may not always provide both forage and nesting resources. We evaluated wildflower plantings designed to augment floral resources to determine their ability to enhance nesting by soil‐nesting bees over 3 study years in Northern California agricultural landscapes. We established wildflower plantings along borders of annual row crops and paired each with an unplanted control border. We used soil emergence traps to assess nest densities and species richness of soil‐nesting bees from spring through late summer at paired field borders planted with wildflowers or maintained conventionally as bare or sparsely vegetated areas, as is typical for the region. We also quantified soil‐surface characteristics and flower resources among borders. Wildflower plantings significantly increased nest densities and the richness of bee species using them. Such benefits occurred within the first year of planting and persisted up to 4 years post establishment. The composition of nesting bee communities also differed between wildflower and unenhanced borders. Wildflower plantings differed from controls in multiple characteristics of the soil surface, including vegetation cover, surface microtopography and hardness. Surprisingly, only vegetation cover significantly affected nest densities and species richness. Wildflower plantings are a widespread habitat action with the potential to support wild bees. The demonstrated benefit wildflower plantings had for increasing the nesting of soil‐nesting bees greatly augments their relevance for the conservation of wild bee communities in agricultural and other landscapes. Identifying soil‐surface characteristics that are important for nesting provides critical information to guide the implementation and management of habitats for bees.

 

Human‐mediated species introductions provide real‐time experiments in how communities respond to interspecific competition. For example, managed honey beesApis mellifera(L.) have been widely introduced outside their native range and may compete with native bees for pollen and nectar. Indeed, multiple studies suggest that honey bees and native bees overlap in their use of floral resources. However, for resource overlap to negatively impact resource collection by native bees, resource availability must also decline, and few studies investigate impacts of honey bee competition on native bee floral visits and floral resource availability simultaneously.

In this study, we investigate impacts of increasing honey bee abundance on native bee visitation patterns, pollen diets, and nectar and pollen resource availability in two Californian landscapes: wildflower plantings in the Central Valley and montane meadows in the Sierra.

We collected data on bee visits to flowers, pollen and nectar availability, and pollen carried on bee bodies across multiple sites in the Sierra and Central Valley. We then constructed plant‐pollinator visitation networks to assess how increasing honey bee abundance impacted perceived apparent competition (PAC), a measure of niche overlap, and pollinator specialization (d'). We also compared PAC values against null expectations to address whether observed changes in niche overlap were greater or less than what we would expect given the relative abundances of interacting partners.

We find clear evidence of exploitative competition in both ecosystems based on the following results: (1) honey bee competition increased niche overlap between honey bees and native bees, (2) increased honey bee abundance led to decreased pollen and nectar availability in flowers, and (3) native bee communities responded to competition by shifting their floral visits, with some becoming more specialized and others becoming more generalized depending on the ecosystem and bee taxon considered.

Although native bees can adapt to honey bee competition by shifting their floral visits, the coexistence of honey bees and native bees is tenuous and will depend on floral resource availability. Preserving and augmenting floral resources is therefore essential in mitigating negative impacts of honey bee competition. In two California ecosystems, honey bee competition decreases pollen and nectar resource availability in flowers and alters native bee diets with potential implications for bee conservation and wildlands management.

 

Introduced species can have cascading effects on ecological communities, but indirect effects of species introductions are rarely the focus of ecological studies. For example, managed honey bees (Apis mellifera) have been widely introduced outside their native range and are increasingly dominant floral visitors. Multiple studies have documented how honey bees impact native bee communities through floral resource competition, but few have quantified how these competitive interactions indirectly affect pollination and plant reproduction. Such indirect effects are hard to detect because honey bees are themselves pollinators and may directly impact pollination through their own floral visits. The potentially huge but poorly understood impacts that non‐native honey bees have on native plant populations combined with increased pressure from beekeepers to place hives in U.S. National Parks and Forests makes exploring impacts of honey bee introductions on native plant pollination of pressing concern. In this study, we used experimental hive additions, field observations, as well as single‐visit and multiple‐visit pollination effectiveness trials across multiple years to untangle the direct and indirect impacts of increasing honey bee abundance on the pollination of an ecologically important wildflower,Camassia quamash. We found compelling evidence that honey bee introductions indirectly decrease pollination by reducing nectar and pollen availability and competitively excluding visits from more effective native bees. In contrast, the direct impact of honey bee visits on pollination was negligible, and, if anything, negative. Honey bees were ineffective pollinators, and increasing visit quantity could not compensate for inferior visit quality. Indeed, although the effect was not statistically significant, increased honey bee visits had a marginally negative impact on seed production. Thus, honey bee introductions may erode longstanding plant‐pollinator mutualisms, with negative consequences for plant reproduction. Our study calls for a more thorough understanding of the indirect effects of species introductions and more careful coordination of hive placements.

 

Biodiversity promotes ecosystem function (EF) in experiments, but it remains uncertain how biodiversity loss affects function in larger‐scale natural ecosystems. In these natural ecosystems, rare and declining species are more likely to be lost, and function needs to be maintained across space and time. Here, we explore the importance of rare and declining bee species to the pollination of three wildflowers and three crops using large‐scale (72 sites across 5000 km²), multi‐year datasets. Half of the sampled bee species (82/164) were rare or declining, but these species provided only ~15% of overall pollination. To determine the number of species important to EF, we used two methods of “scaling up,” both of which have previously been used for biodiversity‐function analysis. First, we summed bee species' contributions to pollination across space and time and then found the minimum set of species needed to provide a threshold level of function across all sites; according to this method, effectively no rare and declining bee species were important to pollination. Second, we account for the “insurance value” of biodiversity by finding the minimum set of bee species needed to simultaneously provide a threshold level of function at each site in each year. The second method leads to the conclusion that 25 rare and eight declining bee species (36% and 53% of all rare and declining bee species, respectively) are included in the minimum set. Our findings provide some of the strongest evidence yet that rare and declining species are key to meeting threshold levels of EF, thereby providing a more direct link between real‐world biodiversity loss and EF.

 

Our simulation-based experiments are aimed to demonstrate a use case on the feasibility of fulfillment of global energy demand by primarily relying on solar energy through the integration of a longitudinally-distributed grid. These experiments demonstrate the availability of simulation technologies, good approximation models of grid components, and data for simulation. We also experimented with integrating different tools to create realistic simulations as we are currently developing a detailed tool- chain for experimentation. These experiments consist of a network of model houses at different locations in the world, each producing and consuming only solar energy. The model includes houses, various appliances, appliance usage schedules, regional weather information, floor area, HVAC systems, population, number of houses in the region, and other parameters to imitate a real-world scenario. Data gathered from the power system simulation is used to develop optimization models to find the optimal solar panel area required at the different locations to satisfy energy demands in different scenarios. 

Conditions experienced early in development can affect the future performance of individuals and populations. Demographic theories predict persistent population impacts of past resources, but few studies have experimentally tested such carry‐over effects across generations or cohorts. We used bumble bees to test whether resource timing had persistent effects on within‐colony dynamics over sequential cohorts of workers. We simulated a resource pulse for field colonies either early or late in their development and estimated colony growth rates during pulse‐ and non‐pulse periods. During periods when resources were not supplemented, early‐pulse colonies grew faster than late‐pulse colonies; early‐pulse colonies grew larger as a result. These results revealed persistent effects of past resources on current growth and support the importance of transient dynamics in natural ecological systems. Early‐pulse colonies also produced more queen offspring, highlighting the critical nature of resource timing for the population, as well as colony, dynamics of a key pollinator.

 

Behavior and organization of social groups is thought to be vital to the functioning of societies, yet the contributions of various roles within social groups toward population growth and dynamics have been difficult to quantify. A common approach to quantifying these role‐based contributions is evaluating the number of individuals conducting certain roles, which ignores how behavior might scale up to effects at the population‐level. Manipulative experiments are another common approach to determine population‐level effects, but they often ignore potential feedbacks associated with these various roles.

Here, we evaluate the effects of worker size distribution in bumblebee colonies on worker production in 24 observational colonies across three environments, using functional linear models. Functional linear models are an underused correlative technique that has been used to assess lag effects of environmental drivers on plant performance. We demonstrate potential applications of this technique for exploring high‐dimensional ecological systems, such as the contributions of individuals with different traits to colony dynamics.

We found that more larger workers had mostly positive effects and more smaller workers had negative effects on worker production. Most of these effects were only detected under low or fluctuating resource environments suggesting that the advantage of colonies with larger‐bodied workers becomes more apparent under stressful conditions.

We also demonstrate the wider ecological application of functional linear models. We highlight the advantages and limitations when considering these models, and how they are a valuable complement to many of these performance‐based and manipulative experiments.