Long-term climatic cycles, such as El Niño Southern Oscillation events, could also play a role, particularly in rainfed systems that we may expect to exhibit stronger variability than their irrigated counterparts. ENSO phases have been shown to induce synchrony in masting systems, but knowledge of ENSO effects on crop plants is largely limited to annual crops. As a primary source of climate variation in Brazil and Iran, ENSO could be a cause of periodic yield in Brazilian tangerine and Iranian apricot . Climate and pest cycles may also interact to produce complex longer-term cycles in crops. If future work confirms a biological basis of long cycles in some crops at a national scale, it would be profitable to understand the extent to which these longer-term crop fluctuations reflect exogenous forcing versus endogenous feed backs . In conclusion, we have found that perennial crops frequently exhibit alternate bearing even at a national scale and that this is especially pronounced in wind-pollinated crops. This pattern is remarkable, given the general assumption that management practices have come to outweigh the ecological drivers that would synchronize country-wide production. Our results suggest that historic yield data present a thus far underused resource for further analyses on the mechanisms of reproductive synchrony across time, space and taxa.
Future work could explore the intraspecific and intraregional differences in synchrony and the degree of overlap and divergence between patterns in natural and managed systems. We encourage strengthened collaborations between theoretical ecologists,drainage gutter applied ecologists and horticulturalists for the mutual benefits of achieving an enhanced understanding of the mechanisms of synchronous interannual variability and promoting stable yields and farmer livelihoods.Bees and other flower-visiting animals provide essential pollination services to many US crops and to wild plant species . Bees contributed an estimated 11% of the nation’s agricultural gross domestic product in 2009 , equal to $14.6 billion per year . Of this, at least 20% is provided by wild pollinators that depend on suitable land for nesting and foraging . As the consumption of specialty fruit and vegetable crops has grown , the demand for pollination services has increased. However, the supply of managed honey bees has not kept pace , due to management challenges and colony losses over the last decade . There is growing evidence that wild, unmanaged bees can provide effective pollination services where sufficient habitat exists to support their populations . They can also contribute to the long-term stability of crop pollination, thereby reducing the risk of pollination deficits from variable supply or activity of honey bees . As a result, wild pollinators should be integrated into crop pollination management plans as a supplement or alternative to managed bees . Despite the agricultural importance of wild bees, there is increasing evidence that multiple species are declining in range or abundance. Some of the most important crop pollinators, such as bumble bees , have declined over past decades in the United States . Among the numerous threats to wild bees, including pesticide use, climate change, and disease , habitat loss seems to contribute to most observed declines .
Indeed, a National Research Council committee on the status of pollinators in North America reported that conserving and improving habitats for wild bees is important for ensuring continued pollination services and food security . Recognizing both the growing need for pollination services and increasing threats to wild bees, a recent presidential memorandum called for a national assessment of the status of wild pollinators and available habitat in the United States . The resulting report sets a goal of 7 million acres of land for pollinators over the next 5 y . However, there has been no assessment at the national level of the current status of native pollinator habitat, where and at what rate this habitat is being degraded, and the impact of these changes on bee populations and the pollination services they provide. A national assessment is challenging because plant–pollinator interactions and dynamics occur at relatively fine spatial scales. Wild bee populations are largely determined by the spatial distribution of habitat resources within their foraging range , and this varies from ∼100–2,000 m . Accordingly, most of our understanding of native bee populations is at the scale of landscapes and local sites. Several field-based assessments of habitat resources for native bee species have been developed at landscape scales . However, the required cost and time to scale this type of field assessment to cover all habitat types and bee species nationwide is logistically challenging and prohibitively expensive. When field observations are lacking, careful use of expert derived data has been shown to provide informative estimates that enable habitat assessments , including studies on pollination . Use of expert opinion may therefore be an efficient path to an initial nationwide assessment of pollinator habitat and abundance in the absence of consistent data across different land categories.
Such an approach must include careful treatment of uncertainty that may arise from differences in expertise among regions, authorities, taxa, and so on . Indeed, a robust analysis of uncertainty, and its implications for assessment findings, is a useful result in itself. It can help orient research toward addressing the most important gaps in our national knowledge of wild bees and their importance for crop pollination. Here, we use a published model of bee abundance and expert knowledge to assess the status, trends, and impact of wild bee abundance and associated uncertainties across the coterminous United States. The spatially explicit model predicts a relative index of wild bee abundance based on local nesting resources and the quality of surrounding forage . We parameterize the model with expert-derived estimates of nesting and forage quality for each of the main land-use types in each of the major ecoregions to construct a probability distribution for each parameter that captures estimates by multiple experts and their uncertainty. We first validate model predictions with bee collections and observations from a variety of landscape settings. We then map bee abundance, its uncertainty, and the agricultural demand for pollination across the United States to address the following questions: What are the current status and trends of wild bee abundance across the coterminous United States? What land use changes have driven these trends over a 5-y period ? Which regions and crops experience relatively low bee abundance compared with crop pollination demands? How does uncertainty in our knowledge affect these predictions? Responses to these questions will inform future research efforts and policy decisions to conserve native bees at the national level and can help guide a coordinated and ongoing nationwide assessment of wild bees.Our model predicts generally high abundances of wild bees in areas rich in resources such as chaparral and desert shrublands,plastic gutter intermediate abundances in temperate forest and grassland/rangelands, and lower abundances in most agricultural areas . Patterns of wild bee abundance and expert uncertainty seem correlated . In fact, whereas most areas with low bee abundance also present low uncertainty, only 5% of areas with high bee abundance have low uncertainty. This suggests that experts are more individually or collectively certain about uniformly poor bee habitats than they are about higher-quality habitats , which can vary in quality over time and space . Between 2008 and 2013, wild bee abundance was consistent in 67% of the US land area . However, our model indicates decreases in 23% of the United States , and these decreases were highly likely in 9% of the United States . Most of the areas of likely decrease occurred in agricultural regions of Midwestern and Great Plains states and in the Mississippi river valley. Eleven states [Minnesota, Texas , Wisconsin , South Dakota , North Dakota , Illinois, Missouri, Nebraska, Oklahoma, Kansas, and Louisiana] collectively accounted for 60% of the areas of predicted decrease in wild bee abundance. Over the 5-y period in these states, corn and grain cropland increased 200% and 100%, respectively, and mostly replaced grasslands and pasture . Bee abundance increased in 10% of the United States and the increase was highly likely in 3% of the country .
Areas of likely increase in bee abundance were found in northern ND, eastern Washington and Pennsylvania , southern Montana, parts of several states in the Great Plains, and in southeastern coastal areas . In these areas, grasslands, pastures, and corn/soy fields were converted to higher-quality habitat, such as shrublands or fallow crop fields .Bee abundance maps can be interpreted as the potential “supply” of pollination services from wild bees. To compare this measure of supply to potential agricultural demand, we calculated the area of pollinator-dependent crops, weighted by each crop’s degree of pollinator dependence, for each US county in 2013 . By comparing the two maps, we identified counties with relatively high supply of wild bees and relatively low demand and, conversely, where high demand occurs in counties with relatively low supply . We identified 139 counties where high demand and low supply coincide and 39 counties where this difference was particularly extreme . All of the 139 counties with a pollinator disparity had relatively low uncertainty for 2013 bee abundance , which indicates that there is high confidence in this mismatch. These counties tend to contain either a significant percentage of area that consists of highly pollinator-dependent crops [e.g., almonds, blueberries, and apples in California , Oregon, and WA, respectively] or large amount of less-dependent crops . To examine changes in the relationship between wild bee supply and pollination demand, we combined the two trend maps . We found that 106 counties have simultaneously experienced increases in demand for pollination services and decreases in wild bee abundance . This represents 54% of the 195 counties that have experienced substantial changes in pollination demand . In 27 of these counties, declines in supply were highly likely , whereas in the remaining 79 counties declines were less certain . In counties of West Coast states and Michigan, increases in demand were mostly driven by increases in specialty crops such as almonds, cherries, blueberries, apples, watermelons, and squash. In contrast, demand increases in the Great Plains and Mississippi Valley were driven by increases in crops, such as sunflower, canola, soybeans, and cotton, with moderate to low pollinator dependency. Trends in our measures of supply and demand vary widely among individual crops . Most crops that require animal pollination have expanded in area between 2008 and 2013, whereas the predicted supply of wild bees in many of these cropped areas has declined. Specialty crops, such as pumpkins, blueberries, peaches, apples, and watermelons, are among the crops that present the strongest mismatch between changes in supply and demand. Others, such as canola, have experienced increases in both supply and demand. Of particular concern for future abilities to meet pollination demands, crops that are most dependent on pollinators tend to have experienced simultaneous declines in supply and increases in demand.Our study is the first to our knowledge to map the status and trends of wild bees and their potential impacts on pollination services across the coterminous United States. By combining a spatial model with expert knowledge, we find highly heterogeneous patterns of both predicted abundance of wild bees and our uncertainty regarding those predictions. We also identify counties and crops of potential concern, where declines in wild bee abundance oppose increased need for crop pollination. These analyses form an important step toward a nationwide understanding of the status of wild pollinators. They can also help focus attention and future research toward regions of high uncertainty and to direct management efforts to areas of major concern. Our mapped index of bee abundance clearly shows that areas of intense agriculture are among the lowest in predicted wild bee abundance. Our predictions are also relatively certain in these areas . This reflects consensus among experts about the low suitability of intensively managed agricultural land for wild bees and is supported by an abundance of previous research on the negative effects of intensive agriculture on bee populations . Areas of bee abundance where declines are most certain tend to have experienced additional conversion of natural land covers to crops, especially corn . These results reinforce recent evidence that increased demand for corn in bio-fuel production has intensified threats to natural habitats in corn-growing regions . For example, a recent land-use simulation found that expansion of annual bio-fuel crops could reduce pollinator abundance and diversity at the state level .