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      Wild bee abundance declines with urban warming, regardless of floral density

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      Urban Ecosystems
      Springer Science and Business Media LLC

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          A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion

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            Bee foraging ranges and their relationship to body size.

            Bees are the most important pollinator taxon; therefore, understanding the scale at which they forage has important ecological implications and conservation applications. The foraging ranges for most bee species are unknown. Foraging distance information is critical for understanding the scale at which bee populations respond to the landscape, assessing the role of bee pollinators in affecting plant population structure, planning conservation strategies for plants, and designing bee habitat refugia that maintain pollination function for wild and crop plants. We used data from 96 records of 62 bee species to determine whether body size predicts foraging distance. We regressed maximum and typical foraging distances on body size and found highly significant and explanatory nonlinear relationships. We used a second data set to: (1) compare observed reports of foraging distance to the distances predicted by our regression equations and (2) assess the biases inherent to the different techniques that have been used to assess foraging distance. The equations we present can be used to predict foraging distances for many bee species, based on a simple measurement of body size.
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              Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery

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                Author and article information

                Journal
                Urban Ecosystems
                Urban Ecosyst
                Springer Science and Business Media LLC
                1083-8155
                1573-1642
                June 2018
                January 31 2018
                June 2018
                : 21
                : 3
                : 419-428
                Article
                10.1007/s11252-018-0731-4
                8ec0d7fb-088a-48b5-8e12-cdd1d7becedc
                © 2018

                http://www.springer.com/tdm

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