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Rader, Romina
- PublicationGlobal dataset of bee and hoverfly body weight (mg) and co-varying traits(University of New England, 2019-02-01)
; ; ;Gagic, Vesna ;Cariveau, Daniel P ;Albrecht, Matthias ;Baldock, Katherine C R ;Freitas, Breno M; ;Holzschuh, Andrea ;Molina, Francisco P ;Morten, Joanne M ;Pereira, Janaely S ;Portman, Zachary M ;Roberts, Stuart P M ;Rodriguez, Juanita ;Russo, Laura ;Sutter, Louis ;Vereecken, Nicolas JBartomeus, IgnasiBody size is an integral functional trait that underlies pollination-related ecological processes. This dataset consists of direct measurements of body size, as dry weight, and the intertegular distance (ITD) of 391 bee species (4035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America and South America. We used Bayesian mixed-models to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism and biogeographic region. In addition, we used ordinary least squares regression to assess intraspecific dry weight ~ ITD relationships for ten bee and five hoverfly species. Including co-variates led to more robust interspecific body size predictions for both bees and hoverflies relative to models with ITD alone. In contrast, at the intraspecific level, our results demonstrate that ITD is an inconsistent predictor of body size for bees and hoverflies. Collectively, these models form the basis of the dynamic R package, 'pollimetry’, which provides a comprehensive resource for allometric pollination research worldwide. - PublicationFuture-proofing the pollination services to insect-pollinated crop production(International Society for Horticultural Science, 2024)
; ;Schmidt, L ;Rocchetti, M ;Wright, D; ;Dingley, A ;Preradovic, J ;Jones, J; ;DeVetter, L W ;Perović, D JDavis, A EFruits and vegetables can vary significantly in their dependence upon insect pollinators to transfer pollen. Raspberry and blackberry are two fruits that are regarded as highly-pollinator dependent. This means that knowledge of pollinator foraging behaviour, efficiency at transferring pollen, and interactions between pollinators, flowers, and the surrounding environment, are all critical factors to understand in depth to ensure that pollination service delivery is optimised. Bees have generally been acknowledged as the most important crop pollinators, yet their efficiency can vary in response to various factors including timing of the visit, previous visits, hive health, flowers available and interactions with other taxa. Further, even though we know other insects visit crop flowers, little is known about the pollination services provided by animals other than bees (i.e., non-bees) and their capacity to transfer pollen effectively. We also have a limited understanding about the number and quality of flower visits required in different cultivars and systems to achieve the best fruit quality. Finally, the resources pollinators require in different seasons and landscapes and the environmental conditions in which berry plants are grown, can also mediate the likelihood of pollination success. This presentation will outline a number of research findings that could be used to support greater resiliency with regard to insect pollination needs of Rubus and Ribes. These include understanding the contribution of different flower visitors and their efficiency in providing pollination services, a greater understanding of pollinator resource needs to improve their longevity in orchard environments, the conditions in which plants are most responsive to pollination service delivery and the importance of collaborations between industry and researchers to manage the system sustainably and to optimise fruit production and quality.
- PublicationThe Productivity and Ecology of Urban Agriculture - Dataset(University of New England, 2019-05-09)
; ; This dataset was created for the thesis 'The Productivity and Ecology of Urban Agriculture'. This thesis addresses two underexplored aspects of UA, namely its productivity and the role that biologically mediated ecosystem services play within it, using UA systems in Sydney, Australia, as case studies.
Chapter 3 data consists of plot logbooks, inputs and yields.
Chapter 4 data relates to the calculations concerning what percentage of overall food requirements Urban Agriculture could provide.
Chapter 5 data consists of floral visitation data and pollination in Urban Agriculture.
Chapter 6 data relates to vertebrate activity within Urban Agriculture and its effects.