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We are pleased to annouce the results of the first IWSG T-shirt competition! We had a wonderful range of designs sent in and thought it was a tough decision, the ExCo Judging panel voted that Chris Heward's "Vanellus" design was the winner! This design can be found on both a standard and fitted style of t-shirt and on a tote bag. Chris will be getting one of these t-shirts himself and has won a year's members to the IWSG.   [caption id="attachment_15899" align="aligncenter" width="330"] Chris Heward created this design for our winter 2021 IWSG t-shirt contest and won! He was declared the outright winner and we thank him for his faboulous design.[/caption] In second place is Alex Dodds with her "Hidden Waders", a wonderfully clever design that the judging panel really liked too. Again this design can be found on standard and fitted t-shirt as well as a tote bag. Alex will be winning a copy of her design on a tote bag as runner up. [caption id="attachment_15902" align="aligncenter" width="330"] This is the running up design by Alex Dodds and shows her lovely use of perspective to hide a world of waders into the outline of another.[/caption]   There were so many lovely designs in this completitions that we've decided to also put up three other designs that were Highly Commended by the panel. These are (in no particular order): Shawkat Khan's "Wader Group", Camilo Carneiro's "Whimbrel" and Marc Giles' "Plover Lover". [caption id="attachment_15905" align="aligncenter" width="330"] From left to right, winners of our inaugural t-shirt design competition run during the winter of 2021-2022: 'Whimbrel' design by Camilo Carneiro, 'Wader Group' by Shawkat Khan and 'Plover Lover' by Marc Gilles.[/caption] Please visit our Teemill website to see the final designs and we hope you are tempted to buy one (or two!): https://waderstudygroup.teemill.com/collection/iwsg-t-shirt-competition-winter-2021/

by Deborah Buehler originally published in Wader Study 128(3) It’s hard to ignore climate change these days. Heatwaves are hotter, floods are fiercer, and some part of the planet is always on fire. In the Arctic, ecosystems based on snow, ice and permafrost are disappearing. These habitats are important breeding grounds for many migratory bird species, particularly waders, and they are vanishing before scientists can determine what the birds need most to survive. Breeding waders are notoriously difficult to study because their nests are well camouflaged and spread out over huge swaths of largely inaccessible tundra. This is where technological advances can help. In this issue of Wader Study, Hoefs and colleagues combine powerful machine-learning algorithms with remote sensing data to build a statistical model that can predict the breeding distribution of the Eurasian Dotterel Charadrius morinellus in northern Sweden.¹ Dotterels are medium-sized waders with striking white eye-stripes and a dove-like appearance. They breed on Arctic or alpine tundra from Scotland to western Alaska, then migrate south to non-breeding areas from North Africa to Iran. [caption id="attachment_15867" align="aligncenter" width="330"] A pair of Eurasian Dotterel Charadrius morinellus in the tundra of northern Sweden. (photo: Christian Hoefs).[/caption] Like many wader species, Dotterel populations are declining, and this species is especially vulnerable because it is specialized to a narrow ecological niche. This same quality makes it an ideal species to study using machine-learning based algorithms. Hoefs and colleagues wanted to use such algorithms to build maps showing where suitable habitat for Dotterels is located. They also wanted to determine which environmental variables, in freely-available remote sensing data, best predicted where Dotterels breed. To do this they used a statistical technique called maximum entropy (or MaxEnt) modelling. MaxEnt is a method that can predict where birds and other organisms are most likely to be located (their distribution) using limited field data. While most predictive methods need to be trained on input about both where the organisms usually are (presence) and where they are not (absence), MaxEnt requires presence data only.² This is good news, because it is easier to gather reliable data on presence than absence. For example, finding a bird, or a nest, definitively indicates presence, but not finding a nest, amid a huge swath of tundra, doesn’t necessarily mean the birds aren’t there. To gather presence data, the researchers surveyed two study areas (~10 km² in total) in the Vindelfjällen Nature Reserve in Swedish Lapland several times during each breeding season from 2016 to 2018. Each visit lasted a full day and a team of three to six people walked through the area in systematic lines regularly scanning with binoculars for birds displaying or showing breeding behavior. This work resulted in a dataset of 23 Dotterel nests and 156 locations where birds were found exhibiting breeding behavior. In the world of statistical modelling, this is a relatively small dataset. The researchers also knew that they were searching for birds in locations that were, necessarily, more accessible to humans (biased sampling) and therefore tended to have similar characteristics (spatial autocorrelation). Luckily, the MaxEnt method can handle small datasets² and biased sampling effort, as long the minimum distance between presence points is set to a coarser scale than predictor variables.³ To meet this requirement, the researchers excluded presence points that were less than 300m apart. This avoided overrepresenting the habitat preferences of birds in more intensively searched areas. MaxEnt modelling also requires a set of environmental variables that describe the suitability of the environment for the species. For this, Hoefs and colleagues used Sentinel-2A satellite data. They needed temporal correspondence between the environmental data and the period when parents raise their chicks, so they used data from July 2018, around the egg hatching date of Dotterels in the area. The satellite data yielded vegetation metrics, texture metrics (grey level textures that show similarities or differences in contrast), and topographic variables. The next step was to determine which of the over 200 environmental variables would provide the best combination of predictors. Often, researchers pre-select variables based on expert knowledge about the biology of the species. But newer techniques, which include everything and then filter to a subset of highly contributing variables, perform better.⁴ The researchers chose this second approach and started with a model that included all available variables. To prune this model, they first removed variables that contributed less than 2%. Then they identified the best-performing variable and removed all variables that were correlated with that variable (the variables change together in similar ways), then repeated with the second-best performing variable and so forth. This process trimmed the set of 211 environmental variables to seven uncorrelated and highly contributing predictors. The researchers now had everything they needed to predict the location of suitable habitat for Dotterel. They used MaxEnt to find the probability distribution of maximum entropy (the most spread out) by comparing known locations of presence against 8,000 background samples randomly distributed over the entire nature reserve to represent potentially unsuitable habitats. The model and maps predicted that about 1% of the total area of the nature reserve (about 60 km²) is suitable habitat for Dotterel. The researchers built and tested their model based on a well-surveyed study area of about 10 km² with about 30 breeding pairs of Dotterel. Extrapolating, this predicts a breeding population of about 180 pairs in the entire nature reserve. Scientists are a skeptical bunch, and the researchers wondered if their model could be trusted. After all, the algorithm chose predictor variables like Chlorophyll Vegetation Index and S08 TM Difference Variance 200 m sd that mean little to humans, whereas other variables like altitude, slope, and exposure, were excluded. To check the model’s results for accuracy against the real world, the authors went back to the field in June 2019 and conducted surveys in areas that the model predicted as suitable Dotterel habitat. They also checked the model against 47 presence locations collected through an independent annual survey conducted in the reserve. The model performed well in the sense that birds were found where they were predicted to be. This result gives some confidence that the variables chosen, and the habitats predicted, by machine-learning are actually important to Dotterels. It also makes sense remembering that the selected variables were highly correlated with things that humans already know are important to Dotterels. The chosen variables might mean less to humans, but they are better predictors of the habitats that Dotterels truly need. Could this approach also work with other species? Perhaps, though the authors caution that this type of modelling is particularly well suited to species, like Dotterel, with very specific habitat requirements and that predictive power might be lower for generalist species. That said, we need all the tools we can get. We are facing serious challenges with climate change and we’re going to have to rely on technology to help. With appropriate validation, species distribution models combined with climate change models might allow us to better predict shifts in suitable breeding habitat and changes in population size for Arctic-breeding birds of conservation concern. This study spotlights the potential power of technology, but also reminds us that technology has limits. The authors were careful to work within those limits and to test the technology against known information before relying on it. We need real-life data to train and ground-truth models. Machines can learn, but humans still need to decide what to teach them, and to interpret what they tell us.   ¹Hoefs, C., T. van der Meer, P. Antkowiak, J. Hagge, M. Green & J. Gottwald. 2021. Exploring the Dotterel Mountains: Improving the understanding of breeding habitat characteristics of an Arctic-breeding specialist bird. Wader Study 128: 226–237. ²Phillips, S.J., R.P. Anderson & R.E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231–259. ³Fourcade, Y., J.O. Engler, D. Rödder & J. Secondi. 2014. Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS ONE 9: e97122. ⁴Zeng, Y., B.W. Low & D.C.J. Yeo. 2016. Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish. Ecological Modelling 341: 5–13.   PDF version of this article is available for download here   Featured Image: Dotterel, Charadrius morinellus, June 2017 ©Hans Norelius from Älvsjö, Sweden.

ÉLVONAL Shorebird Science is happy to announce the V. ÉLVONAL conference “Social behaviour, demography and conservation in shorebirds” during 14–15 January 2022, which will be held as an online meeting. Find attached the conference leaflet as well as the advert to the current PhD position within ÉLVONAL Shorebird Science project:

• V-ELVONAL conference 14-15 January 2022_flyer
• South Bohemia_CZ_PhD_Breeding ecology

The conference will focus on current achievements and future plans of ÉLVONAL teams across the globe and will be enriched with targeted webinars. Any researcher, conservationist or student interested in breeding ecology of shorebirds can use this opportunity to join us from anywhere and discuss recent advances in the field. The conference participation is free of charge and registration is open until 31 December 2021. You can register here: https://forms.gle/rxpGkt7yrTra6PqE9 We are looking forward to meeting you online! Vojtěch Kubelka (on the behalf of the organizing team)   Featured image: Puna Plover (Charadrius alticola) together with wintering Baird’s Sandpiper (Calidris bairdii) at Andean altiplano in Peru. © Vojtěch Kubelka

On behalf of Thomas Lameris & Jeroen Reneerkens  

Dear fellow shorebird researchers, We would like to ask for your assistance in a project, where we aim to analyse how chick growth rates of shorebird species worldwide are impacted by changing climatic conditions. Project background and aim Unusual freezing conditions around the globe during this past winter, followed by record-high temperatures in large parts of the Arctic this spring, again form an example that the globe's climate will be more and more governed by extremes. Vulnerability of shorebirds populations to this changing climate has been predicted from modelling efforts, as well as shown by changes in reproductive success and body size for individual populations. It is likely that birds are especially vulnerable to effects of a warming climate and climatic extremes in early life, during the period of chick growth. We would like to initiate a project to compare chick growth rates in all shorebird species, where we want to make comparisons between species, populations / study sites and years, to study how variation in growth rate is possibly explained by climatic variation. For example, we expect that chick growth rate will be lower when chicks face temperatures below or above their thermoneutral zone, or during extreme climatic conditions such as prolonged periods of rainfall. We hope that this project can give us insights into the vulnerability of shorebirds to a warming climate, and whether species and populations may differ in their vulnerability. Request for data We are looking for data on biometrics (body mass, tarsus length, wing length, etc.) measured for shorebird chicks of any shorebird species. While data collected for chicks with known hatch dates is especially helpful, we consider any data to be useful for this project. We are interested in data from all shorebird species, and from as many study sites, populations and years as possible. This means that any data are valuable, also older data and data collected at atypical sites. We want to use these data specifically to answer the research question outlined above, which is expected to result in one, multi-authored publication, to which collaborators sharing data are invited as co-authors. We consider that data on food availability for chicks (e.g. data on arthropod abundance) is an important explanatory variable when studying chick growth. While we first want to focus on a large-scale comparison in relation to climatic variables only, we consider that a second step would be a comparison with data on food availability. If you have such data available for your population, please let us know and we will get in touch with you on this. Also, if you happen to know the existence of (unpublished) data by others, please forward this message and/or let us know. Please get in touch if you have any questions or comments. Best wishes, Thomas Lameris (thomaslameris@gmail.com) & Jeroen Reneerkens (jeroen.reneerkens@nioz.nl)

The IWSG Small Project Grants Committee have decided to extend the deadline for application to 15th December 2021. With this grant we aim to support shorebird studies that otherwise will not go ahead. This could be all sorts of projects related to waders (shorebirds): ecological and/or conservation research, pilot studies looking at biological aspects of a single or a few species, or counts of staging birds at unexplored sites. Or something completely different! Application is open for IWSG members who have a project idea that could be undertaken if supported with a small amount of money (currently 1000 Euros per project). About the grant: IWSG Small Projects Grants The application form: https://www.waderstudygroup.org/wp-content/uploads/2018/11/IWSG-grant-application_28112018_form-Word.doc   The IWSG Small Grant Committee Yahkat Barshep, Birgita Hansen, Nils Warnock, Vojtěch Kubelka and Jannik Hansen   Featured image: Common Redshank Tringa totanus, April 2017, Lake Geneva, Wisconsin, USA. ©Christoph Müller.

This year, we’d like to encourage you to get your artistic talents flowing by sending in your best designs to go on a T-shirt for IWSG! Currently we only have a few designs in our Teemill shop and we’d love to add to them with ideas from the wider wader and shorebird community. The winner of the competition will win a t-shirt with their design PLUS a year’s members to IWSG whilst the runner up will get a tote bag with their design. All shortlisted designs will be included on our Teemill shop. All proceeds from the sale of bags or clothing will be used to support the running of IWSG. Competition Rules: - Open to all over 18 who are part of the wider wader/shorebird community - Any design will be accepted as long as it has a wader on it, space for the IWSG logo (which can be small) and on a white background - Meaningful text regarding waders will be considered for inclusion. - Enter on which ever artistic medium suits – pencil and paper, water colours, PowerPoint, Photoshop but you will need to be able to scan the final image. Lines must be thick enough to see when printed on fabric (~2mm+) How to enter: - Send a scan of your final design with your name, email & the subject line “IWSG T-shirt Comp” to membership@waderstudygroup.org - Up to 3 entries per person are allowed and should be original and unique artwork - Closing date – midnight 23:59 GMT 1st January 2022. Full Terms and Conditions

The IWSG Small Projects Grants aim to support shorebird studies that otherwise will not go ahead. This could be all sorts of projects related to waders (shorebirds): ecological and/or conservation research, pilot studies looking at biological aspects of a single or a few species, or counts of staging birds at unexplored sites. Or something completely different! Application is open for IWSG members who have a project idea that could be undertaken if supported with a small amount of money (currently 1000 Euros per project). In the below link you can find a description of criteria and the application form. The IWSG Executive Committee has appointed an evaluation committee that will judge the applications, and decide which project will be awarded. Application form: IWSG Small Project Grants Call Applications should be submitted by December 1st 2021, and a decision will be made before 1st of May 2022. Details on the previous recipients of the IWSG Small Grants there: https://www.waderstudygroup.org/projects/small-grants/   [caption id="attachment_15049" align="aligncenter" width="330"] Sandra Giner & Virginia Sanz won the 2021 IWSG Small Project Grant to carry out shorebird survey in Margarita Island, Venezuela. ©Carolina Davila[/caption]

Hunan Global Messenger Technology Co., Ltd. (HQXS) is sponsoring the IWSG Conference 2021 by giving away six GSM/GPS transmitters to one conference participant. How to win the transmitters? Please find out at: https://www.waderstudygroup.org/conferences/2021-virtual-conference/#3

by Deborah Buehler originally published in Wader Study 128(2) Imagine that you’re a Hudsonian Whimbrel Numenius hudsonicus, a relatively large shorebird, about 45 cm from head to tail. The tide is up (which means your workday is over), the sun has set, and now you need a safe place to rest – you and nearly 20,000 others. Where do you go? Can 20,000 large birds hide? In this issue of Wader Study, Sanders and colleagues describe a nocturnal roost site in South Carolina, which supports about 20,000 roosting Whimbrel.¹ That’s nearly 50% of the eastern population and nearly 25% of the entire North American population. A roost is a safe place where a group of birds can settle to rest. Unlike a nesting site, roosts are for respite, not reproduction. For shorebirds, roosting usually happens when the tide is high enough to flood areas where the birds feed. At that point, the birds will fly to exposed dry land to take a break. Because tide times vary, roost times vary, and shorebirds rest by day (diurnal roost) or by night (nocturnal roost). Nocturnal roosts are often farther from mainland beaches and forests than diurnal sites. This offers better protection from nocturnal predators, such as owls, but it also makes these sites harder for both birds and humans to find. One wouldn’t think that 20,000 shorebirds would be easy to hide, but finding nocturnal roost sites is no easy task, even for large, well-studied species in a country relatively well-populated with ornithologists. Sanders and colleagues first discovered roosting flocks of Whimbrel on Deveaux Bank in 2014. Deveaux Bank is a sandbar at the mouth of the North Edisto River in Charleston County, South Carolina. It sits on the northeastern edge of the ACE (Ashepoo, Combahee, and Edisto Rivers) Basin, a 1,420 km² multi-use conservation area. Though the island is about a kilometer squared at low tide, the ephemeral nature of the sandbanks means that only about a quarter of that remains dry at high tide for roosting. [caption id="attachment_15413" align="aligncenter" width="960"] Aerial view of the study site at Deveaux Bank (photo: Andy Johnson/Cornell Lab of Ornithology)[/caption] After finding evidence of the roost, the researchers returned to the site in 2019 and 2020 to find out how many birds used the area and to refine their nocturnal bird counting methodology. The team consisted of experts experienced in conducting surveys and estimating the sizes of large flocks. One to two researchers were stationed at four counting locations around Deveaux Bank allowing them to scan in all directions for arriving Whimbrel (see Fig. 1c in the paper).   Because Whimbrel rest when their feeding areas are covered by the tide, the researchers chose survey dates when high tide was within 125 minutes of civil twilight (the period after sunset when enough natural light remains that artificial light is not needed), so that foraging areas would be underwater near sunset. Also, all but one of the survey dates fell within three days of a full moon, which proved helpful as it allowed counting by moonlight when the sky was clear. Sanders and colleagues began counting as soon as flocks flying towards the sandbar were visible over the water (about 0.5 km away). Once on the sandbar, if the birds were disturbed, for example by a predator, the team subtracted any birds that left from their totals. If they settled again elsewhere, they were counted at the new location. This ensured no birds were double counted.   Not surprisingly, the main challenge in counting birds using a nocturnal roost is darkness. Many nights the researchers could hear that birds were still arriving after civil twilight, but it was too dark to keep counting them. Their nightly counts ranged from 8,974–19,485, with the highest count on a night when the moon was nearly full, and the sky was clear. That night 34% of all Whimbrel counted arrived after civil twilight and were counted by moonlight. It was the only night when counting stopped because birds were no longer arriving, rather than due to darkness.   This study reports several important findings. First, Deveaux Bank – a previously unknown nocturnal roost site – supports at least 19,485 roosting Whimbrel during peak spring migration. Whimbrel numbers have fallen nearly 50% over a 15-year period since the 1990s. Deveaux Bank now presents an opportunity to conserve and study a large part of the Whimbrel population. However, it also presents a risk – a lot of birds relying on a single, ephemeral sandbar for their survival.   Second, the researchers found that Deveaux Bank is likely important over a large area. Birds flew into the roost from all directions over the course of the evenings, first arriving from nearby inland marshes then, hours later, over the water from the south. This suggests that some birds are flying into the roost from long distances, implying that ideal roost sites are limited. Together, these first two findings emphasize the need to discover or create a network of alternative roosting sites for the long-term conservation of the species.   Third, the study spotlights the fact that, though difficult to find, once known, nocturnal roosts provide a way to survey large numbers of birds that would otherwise be uncountable as they forage over huge swaths of saltmarsh. Optimizing methods to count birds at roosts could give researchers a way to get more accurate population estimates and to track how populations are changing over time.   Fourth, this study shows the importance of both tides and lunar phase when choosing dates to count birds at nocturnal roosts. The optimal nights are the ones when high tide happens just before nightfall. Finally, selecting dates close to the full moon can help to ensure that birds arriving after civil twilight can be counted by moonlight if the skies are clear. The researchers recommend survey dates near the spring tide (the highest tides in the month), within two days of the full moon, when civil twilight and high tide are 30–60 minutes apart.   Shorebird populations are in steep decline around the world. By publishing their work, Sanders and colleagues have given us a better understanding of the importance of nocturnal roost sites and how best to survey them once found. Whimbrel are well-studied birds and their roost was found in a conservation area frequented by ornithologists. For less well-studied species migrating through less well-studied areas, far less is known about where birds roost, or even the larger geographic areas that they visit on their journeys. In this issue of Wader Study there are several papers describing the quest to determine where birds go, and which areas are essential to them. For example, Summers and colleagues used geolocator trackers to determine areas important to Wood Sandpipers Tringa glareola on their migrations between Scotland and West Africa.² Adha Putra and colleagues used ground surveys to discover that the eastern coast of Sumatra is a significant wintering area for Nordmann’s Greenshank Tringa guttifer – one of the most threatened shorebird species in the world.³   PDF version of this article is available for download here: https://www.waderstudygroup.org/article/15328/  

1. Sanders, F.J., M.C. Handmaker, A.S. Johnson & N.R. Senner. 2021. Nocturnal roost on South Carolina coast supports nearly half of Atlantic coast population of Hudsonian Whimbrel Numenius hudsonicus during northward migration. Wader Study 128(2): 117–124.

 

2. Summers, R.W., B. Etheridge, N. Christian, N. Elkins & I.R. Cleasby. 2021. Timing, staging, speed and destination of migrant Wood Sandpipers Tringa glareola. Wader Study 128(2): 145–152.

 

3. Adha Putra, C., D. Hikmatullah, I. Febrianto, I. Taufiqurrahman & C. Zöckler. 2021. North Sumatra is an internationally significant region for non-breeding Nordmann’s Greenshanks Tringa guttifer. Wader Study 128(2): 157–164.

Featured image: Video frame of Whimbrel at Deveaux Bank, South Carolina. ©Andy Johnson/Cornell Lab of Ornithology.

Only recently we were hoping to meet in person this year, but the ongoing uncertainties regarding the health emergency have made the decision for us: the IWSG annual conference 2021 will be held online. The meeting will take place from the 8^th until the 10^th of October. For more information, registration and abstract submission, please visit: https://www.waderstudygroup.org/conferences/2021-virtual-conference/.