Beescape FAQ

The Center for Pollinator Research has many resources to help people design better pollinator gardens and habitat, and to reduce pesticide use.

The tool uses the USDA-NASS Cropland Data Layer (CDL) for its base map of what crops and natural habitats are in your landscape. These data are created through a combination of survey work of crop fields by the USDA and satellite collection of land cover data for natural areas. This is the best available national map of US cropland, but it has some inaccuracies at the local level. It provides data at a resolution of 30 meters (about 1/5th of an acre), so it misses detail for land cover and land use at finer scales. Also, the use of satellite information to classify land cover is not perfect so sometimes will misclassify land cover. Finally, it takes about a year to classify the land cover from the satellite and provide the data to the public, so that the base map typically represents the previous year’s data. We use the resulting CDL layer as an input into predictive models that translate the land cover into bee forage resources, nesting habitat, and insecticide toxic load.

Bees require two basic types of resources to survive and thrive in a landscape: nesting substrates (for wild bees) and floral resources (for honey bees and wild bees). Wild bees nest in the ground or in dead plants and trees. If these resources are poor, bees have to fly farther to get what they need.

Beescape translates a map of land cover into a floral quality index (0-100) for each floral season (spring, summer, fall) that represents the density and supply of floral resources provided by each land cover type in the selected landscape. Data used to parameterize the model come from a past study that estimated wild bee habitat quality across the continental United States. In this study, fourteen wild bee experts provided estimates of forage and wild bee nesting quality provided by each land cover type, and we use the average of their estimates to parameterize the translation of land cover into nesting and floral quality values. The model used in this paper has been empirically tested globally and shown to predict wild bee abundance.

The insecticide load score reflects the expected ‘toxic load’ of insecticides applied surrounding a given location (representing a colony or nest site). These scores are generated in a multi-step process. First, we use data on insecticide use from the U.S. Geological Survey and data on crop acreage from the U.S. Department of Agriculture to estimate the average per-hectare use of > 100 insecticide active ingredients on each type of cropland for each state. Insecticide use is then translated into honey bee lethal doses and summed across insecticides to generate a single value expressed in billion lethal doses applied per hectare, which we scaled (x100) to be similar in value to the forage and nesting scores. We use these data in combination with land cover data to generate a map of predicted insecticide toxic load. Higher scores are predicted to negatively influence bee and/or hive health.

There are several limitations and sources of uncertainty in the insecticide load score. Importantly, the score is based on all insecticides applied in a landscape, but does not account for the reality that bees will encounter only a small proportion of the total insecticides applied. Thus, these scores should provide information on the relative amount of insecticide toxicity in the landscape. Moreover, the score reflects agricultural insecticide use, and so excludes other kinds of insecticide application (e.g. homeowner use, mosquito spraying). The score also scales insecticide use by short-term toxicity to adult bees, and assumes that insecticides have additive effects. Sublethal effects, effects on developing bees, and synergistic effects therefore may not be fully captured by this score. Finally, patterns of insecticide use are predicted based on state averages from surveys conducted in recent years and so do not reflect local variability in farmer decision-making.

The climate data comes from the PRISM Climate Group at Oregon State University in the form of monthly average temperatures and monthly precipitation totals. The current year’s data is presented alongside the average values from the previous ten years to help beekeepers account for abnormal weather that may impact winter survival rates.

The economic value of pollinators is calculated based on the types of crops in the selected area, how much those crops depend on insect pollinators to produce seeds, fruits, or vegetables, and the average yield/acre and price for that crop. The data for the average yield/acre and price was provided from the 2012 Census of Agriculture; this is the most recent data available as of 2023.

Beescape calculates to amount of economic value pollinators provide to agricultural crops in your selected area. Some crops, like fruits, vegetables, and tree nuts, depend heavily on insect pollinators. Other crops, such as corn and wheat, are wind-pollinated. In areas with more pollinator dependent crops, the economic value provided by pollinators will be higher.

The actual values for the area you selected can vary greatly, depending on the specific varieties grown, the annual weather conditions, and current market conditions.

Using this approach, our team calculated that pollinators contributed $34 billion to agricultural crop value in the United States in 2012. You can learn more about this study here: https://pubs.acs.org/doi/full/10.1021/acs.est.0c04786

Although the Beescape map can generate predictive landscape quality and insecticide load scores for any point within the contiguous US, it’s important to remember that the model underlying the map tool is not 100% accurate. The model is limited by underlying data sources which include the USDA-NASS Cropland Data Layer, insecticide data from the USGS, information from peer-reviewed research studies and expert opinion.

Landscape changes can happen rapidly and at varying scales. The USDA-NASS Crop Data is used in conjunction with other data to translate land cover data into bee forage resources, nesting habitat, and insecticide toxic load. The USDA-NASS Crop Data Layer is the best available national map of US cropland, but it has some inaccuracies at the local level. It provides data at a resolution of 30 meters (about 1/5th of an acre), so it misses detail for land cover and land use at finer scales. Also, the use of satellite information to classify land cover is not perfect, and sometimes land cover is misclassified. Finally, it takes about a year to classify land cover information captured by satellites and to provide the data to the public. Thus, the base map typically represents the previous year’s data.

There are also several sources of uncertainty in the insecticide load score. Importantly, the score is based on all insecticides applied in a landscape but does not account for the reality that bees will encounter only a small proportion of the total insecticides applied. Thus, these scores should provide information on the relative amount of insecticide toxicity in the landscape. Moreover, the score is limited to agricultural insecticide use, and so excludes other kinds of insecticide application (e.g., homeowner use, mosquito spraying). The score also scales insecticide use by short-term toxicity to adult bees and assumes that insecticides have additive effects. Sublethal effects, effects on developing bees, and synergistic effects therefore may not be fully captured by this score. Finally, patterns of insecticide use are predicted based on state averages from surveys conducted in recent years and do not reflect local variability in farmer decision-making.