Although Willis et al. found no difference in average counts between experts and non-experts, non-expert counts tended to be more variable per specimen. This in part depended on the specimen being assessed—specimens with more objects to count had higher error rates. As with any crowdsourcing project, care should be taken when choosing which specimens and taxa to include . Additionally, CrowdCurio is in the process of implementing additional features to improve data quality, such as filtering users based on their ability to repeat the same task. The phenological data generated within CrowdCurio can be expressed according to the protocol outlined in this paper and shared via Darwin Core Archives.One ultimate goal is to combine herbarium specimen data with other sources of phenological data to make possible the detection of phenological changes across geographic, temporal, and taxonomic scales. The PPO provides an opportunity for herbarium data to be combined with disparate data sources, such as in situ phenological monitoring or satellite imagery. The PPO is a common vocabulary for describing plant phenological traits and was designed to provide a means to support global-scale integration of phenological data.
Ontologies provide highly structured, greenhouse vertical farming controlled vocabularies for data annotation and are particularly useful for standardization, because they not only establish a common terminology but alsoformalize logical relationships between terms such that they can be analyzed using machine reasoning. For example, logical term relationships in the PPO specify that any plant with “expanding leaves” must necessarily also have “non-senescing leaves.” This logical structure means that data can be integrated at different levels of detail and software can be used to establish new facts about the data that were not expressed in the original data sets. This structure in turn enables large-scale integration among a wide range of study types, including: studies addressing similar phenophases but using different methodologies, studies involving different phenophases, and studies not specifically addressing phenology but producing other types of data . Thus, the PPO empowers researchers to aggregate larger data sets, at the global scale, and to address broader questions involving the interplay of phenology and other factors. Accordingly, the PPO is already being used to integrate data resources such as those from the USA National Phenology Network , the Pan-European Phenology Network , and herbarium digitization efforts.
The PPO and associated integration tools are compatible with the Darwin Core and Apple Core standards and associated data-sharing tools discussed above. Never before has an understanding of phenology been so important to humans. We are in a time of massive environmental change, and the organisms upon which we depend will have to adapt or migrate if they are to avoid local or global extinction. We need phenological data from specimens now more than ever, and researchers are ready and eager to analyze high-quality data sets, particularly those comprising high taxonomic diversity, temporal depth, and a broad geographic range. With minimal additional efforts during or post-digitization, specimens can be scored quickly and easily and contribute to our understanding of our changing planet and the flora that sustains it.Competition occurs when species vie for a common but limited resource , leading to decreased population growth of species that fail to appropriately shift their resource use . Ample evidence suggests that competition can alter the structure and function of ecological communities , and ecological theory predicts that two perfectly similar species cannot coexist without one species competitively displacing the other . Yet, there remains considerable debate regarding the degree to which competition drives species evolution and extinctions . Understanding when and where overlapping resource use might eventually lead to competitive displacement is especially important in managing the impacts of exotic species. For example, hyper-generalist honey bees have been introduced into many ecosystems outside of their native range and often overlap with other bees in their use of floral resources .
However, shared use does not automatically indicate that competitive displacement is occurring. Nectar production and replenishment rates vary widely among and within plant species , as does pollen production and floral resources may not be limited if flowers are abundant or if rates of resource extraction equal rates of replenishment.Assessing honey bee vs. wild bee competition is further complicated by the fact that bees may respond to competitive pressures by shifting floral visits to alternative floral resources or by narrowing their diet breadth . As such, a snapshot of resource use may indicate that competitive displacement has occurred, but niche partitioning will not negatively affect the fitness of displaced species unless the quantity and quality of resources collected also declines. As such, knowledge of resource use overlap alone is insufficient to determine whether honey bee competition might have negative consequences for native bee populations . Indeed, although we know that honey bees collect massive amounts of pollen and nectar from flowers , whether such resource collection alters floral resource availability remains poorly tested. Many different studies have assessed competition using many different assessment tools . Field studies provide ample evidence that honey bee competition can alter wild bee visits to plants and restructure the community of interaction among plants and pollinators . At the level of individual foragers, competition among bumble bees can increase floral fidelity and conspecific pollen transport . Although such questions have yet to be investigated in the context of honey bee competition, honey bee abundance can decrease niche breadth at the species-level and parallel changes may be occurring at the individual-level. A few studies have measured the impact of honey bee abundance and apiary proximity on floral resource availability and floral resource collection by native bees. These studies, in concert with field studies of floral visitation patterns, have considerably advanced our understanding of honey bee competition impacts. However, no studies investigate changes in resource availability and resource use shifts simultaneously. Exploitative competition occurs when resource collection by one species negatively impacts resource collection by another species . Thus, studying impacts of increased honey bee abundance on both resource availability and resource use would provide a more complete picture of whether exploitative competition is truly occurring. Perhaps more importantly, such information gets us much closer to understanding whether competition might have negative fitness consequences for displaced species. For example, nft vertical farming if resource availability declines but visitation patterns remain static, there may be few pathways for native bees to behaviorally escape competition by using different resources. On the other hand, without evidence of declining resource availability, one cannot assume that exploitative competition is responsible for shifting interaction pattens. Understanding when and where honey bees compete with wild bees for floral resources has important consequences for agricultural pollination, honey bee management, and conservation policy. Honey bees contribute billions of dollars to the U.S. economy as crop pollinators and wildflower honey is a highly valuable agricultural commodity. However, native bees are also important pollinators, particularly for crop species not efficiently pollinated by honey bees and the integration of managed and wild bees can additively and synergistically improve crop yields . The most popular strategies for supporting honey bees and native bees include planting wildflowers in agricultural landscapes and preserving floral resources in natural landscapes.Indeed, abundant and diverse floral resources may prevent summer colony losses and mitigate negative impacts of disease and pesticide exposure . Unfortunately, floral resources are rapidly disappearing from agricultural landscapes in the United States , increasing interest among beekeepers in pasturing hives in more verdant natural landscapes .
However, scientists and conservation groups worry that non-native honey bees will compete with native bees for pollen and nectar resources , potentially endangering imperiled native bee species . In natural landscapes, and especially on public and protected lands in National Parks and Forests, co-managing for honey bees and native bees by planting sufficient flowers is not a management option. Instead, we must determine how, where, and when honey bees compete with native bees to guide decisions around hive densities and apiary locations. Our objective for this study was to assess whether honey bees compete with wild native bees for pollen and nectar resources using complementary measures of floral resource use and floral resource availability in two contrasting Californian landscapes: montane meadows in the Sierra mountains and wildflower planting neighboring almond orchards in the Central Valley. Both systems provide important floral resources to native bees but are also heavily used by managed honey bees. Wildflower plantings support honey bees immediately after almond pollination contracts and montane meadows provide abundant floral resources for summer honey production. As such, evaluating potential for competition is key to ensuring sustainable shared use of these landscapes. Using plant-pollinator visitation networks and data on the composition of pollen on native bee bodies, we asked whether increased honey bee abundance led to changes in apparent competition between honey bees and wild bees, wild bee specialization, and network-level complementary specialization. We also assessed whether wild bee pollen fidelity, pollen diet diversity, and pollen diet composition responded to changes in honey bee abundance. Lastly, we asked whether honey bee abundance influenced pollen and nectar availability in key flowering species from each system.We conducted this work in the California Central Valley at 5 replicated wildflower plantings neighboring almond orchards which we sampled in 2017 and 2018. We also sampled 15 meadows in the Central Sierra in 2019. In both ecosystems, some variation in honey bee abundance was due to site proximity to commercial apiaries. In the Sierra, we also experimentally supplemented three meadows initially free of honey bees with 20 hives. A full description of honey bee treatments in the Sierra is described in Page and Williams 2022 . For our Central Valley wildflower plantings, site selection and wildflower establishment methods are described in Rundlöf et al. . Sites averaged 1.6 km to the nearest neighboring site in the Sierra and 11.3 km to the nearest neighboring site in the Central Valley. Within each ecosystem, sites were in consistent landscape contexts and drew from the same regional species pools of native pollinators. In the Central Valley, we surveyed pollinators and their visits to flowering plants over four sample rounds from April – May. In the Sierra, we sampled sites from May – July. Most sites were sampled two to four times, but some sites were sampled up ten times if the blooms of Camassia quamash and Penstemon rydbergii lasted long enough. In the Central Valley, we netted insects actively visiting flowers during 10-minute walks of two 100 m2 transects which were each sampled once in the morning and once in the afternoon . In theSierra, we sampled one-hectare subplots that varied in floral species composition, netting active flower visitors while walking 100 m2 transects for two 30-minute periods in the morning and the afternoon . In both systems, we netted exclusively on sunny or partly cloudy days when average wind speeds were below 5 m/s and temperatures were above 13º C. Netted pollinators were collected individually in separate collection vials to minimize pollen contamination and euthanized using dry ice, except for bumble bee queens, which we identified on site and then released. In both systems, we collected up to twenty honey bees during netting transects and counted any additional honey bees. Native bee specimens were identified to morphospecies by expert taxonomists . For network analyses, we excluded bees not identified to morphospecies . Because we were exclusively interested in documenting patterns of honey bee vs. native bee competition, we also excluded non-bee floral visitors from network analyses.In the lab, we swabbed specimens with fuchsin-tinted gelatin cubes which we then melted onto microscope slides. We counted and identified pollen grains carried on bee bodies using a compound light microscope and pollen reference collections. We calculated pollen fidelity as the number of pollen grains from the plant species from which the specimen was caught divided by the total number of pollen grains in the swabbed sample. Most pollen was identified to species, but we sometimes grouped pollen grains at the genus level. We calculated pollen diversity using the Shannon-Weiner diversity index .We assessed whether honey bee abundance in wildflower plantings, measured as the total number of honey bees visiting flowering plants during morning and afternoon netting transects, was associated with perceived apparent competition , wild bee specialization , and complementary specialization using separate generalized linear mixed effects models for each network metric and each ecosystem.