United States

Animal diet breadth varies along a continuum, from extreme specialization (foraging on a few or one food type) to extreme generalization (foraging on many different food types). Greater diet breadth is frequently associated with reduced extinction risk. Pollinators such as bees are essential in natural and agricultural landscapes and many species are declining rapidly. Most bee species are thought to be highly specialized to feeding on the pollen of specific plant species, which could increase their extinction risk. Currently, we are experiencing a pollination crisis, with perhaps the majority of pollinator species declining at a rapid rate. However, we currently lack a consolidated accounting of how pollen diet breadth varies across the approximately 20,000 bee species. In this study, we are conducting a literature search to determine the pollen diet breadth of as many bee species as possible. Over 1700 bee species and their pollen hosts have been recorded in our database so far. Our records indicate that of these bee species, around 5% are extreme specialists (monolectic) and a further 73% are strongly specialized (oligolectic); only around 22% of the bee species are extreme generalists (polylectic). On average, bees used 1.4 plant families, 2.6 genera, and 2.6 species as pollen hosts. Diet breadth across all bee species ranged from 1-49 plant families, 1-96 genera, and 1-61 species. Characterizing diet breadth across the bees not only aids in conserving bees, but helps guide conservation of the plants on which bees forage.

Molsamp 2021

Plant Host Specialization By Bees and Implications For Conservation

Welcome Seabirders!  

Welcome to Virtual World Seabird Conference 3 - vWSC3! Whether you are in your office or lab, at home, in a coffee shop or bar poaching some wifi, or at a remote field site or research vessel – we are very excited to welcome you to the third ever World Seabird Conference. 

We would like to thank ALL of you for being so patient as WSC3 was scheduled, postponed, rescheduled, revised to virtual, and scheduled again. Throughout all those iterations there was one message that remained perfectly clear – seabirders were eager to meet and share their science. If we could not meet in person then virtual it would have to be, but a 3rd WSC was something everyone wanted. That support and commitment helped the WSU Board of Directors and Member Societies sort through all of the challenges they faced to plan and hold this conference. 

The list of those that need to be thanked is long and, while we plan on recognizing many during the live closing plenary, it is important to do so here in writing as well. 

The Australasian Seabird Group was our Local Host for our plan to meet in Hobart, Tasmania. They invested substantial time and effort to find venues and plan events that we unfortunately were not able to visit. Nonetheless we appreciate their work on behalf of WSC3 and encourage all of you to thank them when you see their members in Gathertown or elsewhere during our virtual meeting. Their willingness to host created the initial excitement for WSC3 and without that our vWSC would not have been possible.

We also wish to thank the Science Program Committee, the Virtual Committee, and the Early Career Scientist Committee for their hard work planning the logistics, events, and schedule for vWSC3. These committees also had to deal with changing parameters and short timelines that made what is always a challenging task even more challenging. The Travel Awards Committee also invested time and effort in developing procedures for awarding travel funds that ultimately would not be implemented. 

Our ability to shift from an in-person to a virtual meeting, and to do so in a way that would be financially feasible, was due to the effective efforts of The International Fundraising Committee and to our financial sponsors. The IFC raised funds to support WSC3 and then, through the good relationships they built with sponsors, ensured we could re-envision how those funds could be used to support a virtual conference that would be affordable and high-quality.

We all owe the WSU Board of Directors and the Representatives of the Member Societies a great deal of thanks. They are the ones who manage the WSU and, for the past 18 months, have had to have a series of challenging meetings and conversations, have had to make a series of difficult choices, have had to do all of that while considering the short- and long-term health of WSU and the World Seabird Conferences, and did this while also managing their own challenges at their day jobs. We are grateful for their diligence, patience, foresight, and throughout all of the meetings, their collegiality. Also – a 6-year term is quite a commitment!

There would not be a WSC3 without a successful WSC1 and WSC2. Thanks go to the Pacific Seabird Group for their support of WSC1 in Victoria, Canada, and to the African Seabird Group for their support of WSC2 in Cape Town, South Africa. In each of these endeavors and for our current conference we were fortunate to work with a dependable and trustworthy partner in Podium Conferences. Michelle Smith and Marischal de Armond have become valued members of our team and have not only helped us plan conferences but have assisted and advised the WSU Chairs and Board on issues above and beyond conference planning. 

As we embark on our vWSC3 week we extend to all of you our thanks for showing up, for being patient, and most importantly for the work you do with seabirds. We are all part of a unique, global community that shares an interest, a fascination, and a passion for birds that make a living in our world’s oceans. We have advanced the science, conservation, and management of seabirds as well the ecosystems they inhabit. We are consistently impressed and motivated by the work you do. 

The WSU formed in 2010 because we saw the need for a global organization to address challenges at a global level. Over the past 11 years WSU has grown, adapted, and evolved to become the community that this week is making vWSC3 a reality. Enjoy the week, appreciate and support the friends and colleagues you have made in the community, and if you see us in a virtual hallway please stop and say hello! 

Thank you for the opportunity to serve all of you and the WSU over the past few years,

Nicholas Carlile, Interim Chair, WSU<br>
Patrick Jodice, 2nd Chair of the WSU<br><br>

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3rd World Seabird Conference

Join us for four days of science, networking and virtual engagement with delegates from around the world!

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https://www.dropbox.com/s/uy7tgnb198uiz0o/Abstract_Hamdan_FinalDraft.docx?dl=0

Machine Learning Approaches to Allow Unbiased Analysis of Opioid Withdrawal.

The goal of this project is to investigate the correlation between discharge and drainage basin area with the hope of being able to create a simple equation relating the average discharge from a spring, to the drainage area feeding that spring. Having such a relationship would allow us to measure discharge from any given spring and estimate the drainage area flowing to that spring. This is helpful in the event of a pollution event occurring within a spring and land managers wondering where the pollution may have come from and can travel to. Study locations include springs on Ward Branch Creek, Doling Park, Silver Springs, Smallin Cave, and Jones Spring. Doling Cave and Jones Spring are home to caves, and water flows exit their respective caves. Smallin Cave, Jones Spring and Doling Park (Giboney Cave) have dataloggers recording water temperature about every 15 minutes. Ward Branch Creek, and Silver Spring do not have temperature loggers. Having temperature-loggers can give insight on whether those sites are being fed by deeper groundwater flow, shallow groundwater, or both. Flow volume is calculated on every site except Smallin Cave. Initial data shown opposite trends in temperature between Doling Park’s cave, and Jones Spring Cave with the introduction of moderate precipitation. The spring’s temperature typically indicates whether the spring is fed by a shallow drainage system (caves or similar) or by a deeper (and larger) groundwater aquifer. Using this information, the discharge volumes will help us sort out smaller drainage basins from larger groundwater systems. We will be using the equation Q=KA^C, to estimate discharge, (“Q”) in ft³/sec. We will be graphing upstream drainage areas (“A”), against baseflow (“Q”), and plotting each spring on the graph. We hope to find a good line of correlation. If there is a good line of best-fit, the slope of that line will equal our (“K”) factor within the full equation. This equation has been used in various other hydrologic studies and practices to estimate discharge amounts in various locations (Galster & Pazzaglia & etc., 2006). Initial data shows that baseline flow for Doling Park and Jones Spring Cave are 4ft^3/sec for Doling Park, and 7.2ft^3/sec for Jones Spring. We have found that Jones Spring consistently drops in temperature with the introduction of precipitation (substantial rain). However, Doling Park has shown it is much more radical, and has little to no relation in temperature trends to Jones Spring. This data so far gives us some insight on the similarities and differences between 2 of our locations. In conclusion, this new data can prove beneficial to the cities and communities on The Springfield Plateau in regard to the movement of water, and the study of groundwater in Springfield Missouri.  

Temperature and Discharge Monitoring of Springs and Streams to Approximate Water Drainage Basins in The Springfield Plateau, Missouri

Current screening procedures for lung cancer involve the use of low-dose computed tomography (LDCT). However, this approach has correlated with high false-positive rates, invasive and costly workups. In addition, 80% of diagnosed patients are unresponsive to treatment. There is a need for biomarkers with improved diagnostic accuracy and a capability of predicting response in order to improve treatment. In this study, a set of three miRNAs have been identified that can faithfully differentiate between disease free and lung cancer patients. These miRNAs have also shown to converge on pathways responsible for promoting onceogenesis pf lung cancer and mediating resistance, suggesting potential to serve as a predticitve diagnostic tools.

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Machine Learning Approaches to Allow Unbiased Analysis of Opioid Withdrawal.

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