High resolution prediction maps of solitary bee diversity can guide conservation measures

Wild bees are key ecosystem components making their decline a cause for concern. An effective measure to increase wild bee diversity is to enhance plant diversity. However, the effect on bee diversity of augmenting plant diversity depends on site-specific environmental conditions. We aimed to make spatial predictions of where: (a) environmental conditions maximize bee diversity, so that such areas can be prioritized for augmenting plant diversity; and (b) populations of threatened wild bee species are most likely to occur. We surveyed bee communities in traditionally managed hay meadows in SE Norway and modelled bee diversity as a function of climate, habitat area, and distance to nesting substrates. We used independent data to validate our predictions and found that plant and predicted bee species richness together explained 76% and 69% of the variation in observed solitary bee species richness in forested and agricultural ecosystems, respectively. In urban areas, the predicted bee species richness alone explained 31% of the variation in observed solitary bee species richness. Using data from online species occurrence records, we found that – compared to species of lower conservation concern – threatened solitary bee species were more typically recorded in areas with a high predicted solitary bee species richness. We show that spatial predictions of bee diversity can identify sites where augmenting plant diversity is likely to be most effective. Maps of predicted bee diversity can guide species surveys and monitoring projects and increase the chances of locating populations of threatened bees.publishedVersio

Generic ecological impact assessments of alien species in Norway: a semi-quantitative set of criteria

The ecological impact assessment scheme that has been developed to classify alien species in Norway is presented. The underlying set of criteria enables a generic and semi-quantitative impact assessment of alien species. The criteria produce a classification of alien species that is testable, transparent and easily adjustable to novel evidence or environmental change. This gives a high scientific and political legitimacy to the end product and enables an effective prioritization of management efforts, while at the same time paying attention to the precautionary principle. The criteria chosen are applicable to all species regardless of taxonomic position. This makes the assessment scheme comparable to the Red List criteria used to classify threatened species. The impact of alien species is expressed along two independent axes, one measuring invasion potential, the other ecological effects. Using this two-dimensional approach, the categorization captures the ecological impact of alien species, which is the product rather than the sum of spread and effect. Invasion potential is assessed using three criteria, including expected population lifetime and expansion rate. Ecological effects are evaluated using six criteria, including interactions with native species, changes in landscape types, and the potential to transmit genes or parasites. Effects on threatened species or landscape types receive greater weightings

High resolution prediction maps of solitary bee diversity can guide conservation measures

Wild bees are key ecosystem components making their decline a cause for concern. An effective measure to increase wild bee diversity is to enhance plant diversity. However, the effect on bee diversity of augmenting plant diversity depends on site-specific environmental conditions. We aimed to make spatial predictions of where: (a) environmental conditions maximize bee diversity, so that such areas can be prioritized for augmenting plant diversity; and (b) populations of threatened wild bee species are most likely to occur. We surveyed bee communities in traditionally managed hay meadows in SE Norway and modelled bee diversity as a function of climate, habitat area, and distance to nesting substrates. We used independent data to validate our predictions and found that plant and predicted bee species richness together explained 76% and 69% of the variation in observed solitary bee species richness in forested and agricultural ecosystems, respectively. In urban areas, the predicted bee species richness alone explained 31% of the variation in observed solitary bee species richness. Using data from online species occurrence records, we found that – compared to species of lower conservation concern – threatened solitary bee species were more typically recorded in areas with a high predicted solitary bee species richness. We show that spatial predictions of bee diversity can identify sites where augmenting plant diversity is likely to be most effective. Maps of predicted bee diversity can guide species surveys and monitoring projects and increase the chances of locating populations of threatened bees