Motus wildlife tracking system (Sjoerd Duijns)
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Sinds de jaren 60 wordt radiotelemetrie gebruikt om diverse soorten te volgen in tijd en ruimte.
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Motus wildlife tracking system (Sjoerd Duijns)
- 1. Sjoerd Duijns, Alexandra Anderson, Yves Aubry, Amanda Dey, Scott Flemming, Charles Francis, Christian Friis, Cheri Gratto-Trevor, Diana Hamilton, Rebecca Holberton, Stephanie Koch, Ann McKellar, David Mizrahi, Christy Morrissey, Sarah Neima, David Newstead, Larry Niles, Erica Nol, Julie Paquet, Jennie Rausch, Lindsay Tudor, Yves Turcotte & Paul Smith Motus wildlife tracking system: tracking op continentale schaal
- 2. Automatische VHF telemetrie • Ontvangers: • Toren + antenne • Autonoom • Programeerbaar • Scan meerdere antenne’s en frequencies • Data-opslag (ID, tijd, signaal sterkte, antenne, etc.) • 3G of SD kaart
- 4. SensorGnome: Hoe werkt het? • “geprogrammeerde” VHF zenders • Database: • Frequency offsets • Burst interval (piepjes per tijdseenheid) • Continue ‘luisteren’ naar tags • Zoekt in database naar een match • Wanneer mogelijk, vebinding met internet voor een live feed van de data
- 5. Zenders • 150.100 MHz (Europa) • ~0.2 g tot ~2.6 g • levensduur van 20 dagen tot 928 dagen (afhankelijk van grootte en interval)
- 6. • CTT Life Tags • Ontwikkeld door Cornell University • Zonnepaneel, geen batterij • ~4 billion unieke codes • Vanaf 0.45g • Werken nog niet ‘s nachts • GPS-VHF Beacons • VHF Beacons Kunnen data opslaan (temperatuur, activiteit) • Data kunnen opgepikt worden zodra ze in de buurt van een toren zijn Nieuwe ontwikkelingen
- 7. Motus in aantallen • ~ 900 stations verspreid over 28 landen (9- 76°latitude) • 285 projecten met ~ 700 partners • ~ 22,000 individuen gezenderd • >200 soorten (vogels, vleermuizen, insecten) • ~ 700 million detecties • 80+ publicaties • ~ $100 miljoen CAD
- 8. Groei van aantal ontvangststations
- 9. Waarom gebruiken we motus voor steltloper onderzoek? • Stopover en individuele verblijftijd • Timing van vertrek en aankomst • Bewegingen langs de kust • Migratie afstanden • Migratie snelheden • Migratie routes • Overleving • In kaart brengen van migratie Netwerken
- 12. • Insert red knot video
- 13. • Grote variatie in timing en routes Heeft het te maken met conditie? Voedsel in DB staat onder druk • Hogere kans op overleving (Baker et al. 2004. Proc R Soc B) • Verhoogde mate van wind selectiviteit (Åkesson & Hedenström 2000. Behav Ecol Sociobiol) • Snellere migratie over korte afstanden (Sjöberg et al. 2015. Anim Behav) Negatieve populatie ontwikkeling
- 14. •Residuals van een GLMM (gewicht tegen datum en vleugel als correctie en jaar als random effect) Duijns et al. 2017. Proc R B
- 15. Duijns et al. 2017. Proc R B relative body condition
- 16. Duijns et al. 2017. Proc R B
- 17. Mate van overleving? Duijns et al. 2017. Proc R B
- 18. Stopover Anderson et al. 2019. Frontiers in Ecol and Evol
- 19. Hoe zwaarder hoe korter mass LengthofstayinJamesBay Anderson et al. 2019. Frontiers in Ecol and Evol
- 20. Migratie gaat sneller in voorjaar tegenover najaar Baird Sandpiper basa Dunlin dunl Little Stint list Sanderling sand Semipalmated Sand. sesa Temminck Stint test White-rump wrsa (drawings from birdguid 60% 70% 80% 90% 100% basa_bylo_17 basa_bylo_16 dunl_hoch_17 dunl_barr_17 dunl_sabe_17 dunl_zack_15 dunl_amma_17 dunl_sabe_16 dunl_amma_15 dunl_barr_16 dunl_zack_16 dunl_amma_16 dunl_chur_17 dunl_chur_16 list_bely_17 list_sabe_17 list_sabe_16 list_bely_16 sand_hoch_17 sand_zack_17 sand_zack_15 sand_kvpe_17 sand_zack_16 sand_hoch_15 sand_kvpe_16 sand_kvpe_15 sand_hoch_16 sesa_barr_17 sesa_barr_16 test_sabe_17 test_erku_15 test_erku_17 test_sabe_16 test_erku_16 wrsa_eaba_16 wrsa_eaba_17 wrsa_bylo_17 Duijns et al. 2019. Scientific Reports
- 21. Baird Sandpiper basa Dunlin dunl Little Stint list Sanderling sand Semipalmated Sand. sesa Temminck Stint test White-rum wr (drawings from birdgu 60% 70% 80% 90% 100% basa_bylo_17 basa_bylo_16 dunl_hoch_17 dunl_barr_17 dunl_sabe_17 dunl_zack_15 dunl_amma_17 dunl_sabe_16 dunl_amma_15 dunl_barr_16 dunl_zack_16 dunl_amma_16 dunl_chur_17 dunl_chur_16 list_bely_17 list_sabe_17 list_sabe_16 list_bely_16 sand_hoch_17 sand_zack_17 sand_zack_15 sand_kvpe_17 sand_zack_16 sand_hoch_15 sand_kvpe_16 sand_kvpe_15 sand_hoch_16 sesa_barr_17 sesa_barr_16 test_sabe_17 test_erku_15 test_erku_17 test_sabe_16 test_erku_16 wrsa_eaba_16 wrsa_eaba_17 wrsa_bylo_17 Langere stopovers in het najaar Duijns et al. 2019. Scientific Reports
- 22. Airspeed (snelheid gecorrigeerd voor wind) is hoger in het najaar Baird Sandpiper basa Dunlin dunl Little Stint list Sanderling sand Semipalmated Sand. sesa Temminck Stint test White-rumpe wrsa (drawings from birdguid 60% 70% 80% 90% 100% basa_bylo_17 basa_bylo_16 dunl_hoch_17 dunl_barr_17 dunl_sabe_17 dunl_zack_15 dunl_amma_17 dunl_sabe_16 dunl_amma_15 dunl_barr_16 dunl_zack_16 dunl_amma_16 dunl_chur_17 dunl_chur_16 list_bely_17 list_sabe_17 list_sabe_16 list_bely_16 sand_hoch_17 sand_zack_17 sand_zack_15 sand_kvpe_17 sand_zack_16 sand_hoch_15 sand_kvpe_16 sand_kvpe_15 sand_hoch_16 sesa_barr_17 sesa_barr_16 test_sabe_17 test_erku_15 test_erku_17 test_sabe_16 test_erku_16 wrsa_eaba_16 wrsa_eaba_17 wrsa_bylo_17 wrsa_iglo_17 ~ 10% toename in energetische kosten Duijns et al. 2019. Scientific Reports
- 23. Predatie risico?
- 24. Effecten van wind? Baird Sandpiper basa Dunlin dunl Little Stint list Sanderling sand Semipalmated Sand. sesa Temminck Stint test White-rumped Sand. wrsa (drawings from birdguides.com) 60% 70% 80% 90% 100% basa_bylo_17 basa_bylo_16 dunl_hoch_17 dunl_barr_17 dunl_sabe_17 dunl_zack_15 dunl_amma_17 dunl_sabe_16 dunl_amma_15 dunl_barr_16 dunl_zack_16 dunl_amma_16 dunl_chur_17 dunl_chur_16 list_bely_17 list_sabe_17 list_sabe_16 list_bely_16 sand_hoch_17 sand_zack_17 sand_zack_15 sand_kvpe_17 sand_zack_16 sand_hoch_15 sand_kvpe_16 sand_kvpe_15 sand_hoch_16 sesa_barr_17 sesa_barr_16 test_sabe_17 test_erku_15 test_erku_17 test_sabe_16 test_erku_16 wrsa_eaba_16 wrsa_eaba_17 wrsa_bylo_17 wrsa_iglo_17 wrsa_iglo_16
- 25. Migratie van insecten Knight et al. 2019. Biology Letters • Snellere migratie bij toenemende temperatuur en rugwind • Monarch 143 km op 1 dag (31 km/uur) • Keizerlibel 122 km op 1 dag (max 77 km/uur)
- 27. Tellingen zijn efficient grote aantallen in tijd en ruimte Maar hebben een bias, nl: • Verblijftijd • ‘frame bias’ Het probleem
- 29. Verblijftijd verminderd met de helft; de telling ook gehalveerd
- 30. Verblijftijd verminderd met de helft; de telling ook gehalveerd
- 31. Steenloper -6%/year 0%/year 1974-2013 Frame bias of verandering in verspreiding
- 32. • Zender een deel van de populatie buiten je telgebied (bv broedgebied), en meet het % dat door je gebied komt • Meet de verblijfsduur voor je sample Aantal vogeldagen = Aantal vogels Gemiddelde dagen per vogel Gemiddelde telling * duur = Aantal vogeldagen Aantal vogels % in telgebied = Populatie schatting De oplossing
- 35. Bedankt!
Editor's Notes
- Brief summary stats.
- Here are two years of data, which have been pooled together to calculate survival of migrating knots and for the first time we were able to prove that a knots survival, the chance of it returning after a successful breeding season, was determined by their body condition when leaving Delaware Bay. You’ll notice however that our coverage stops largely stops on the eastern seaboard. Therefore we had to go to the end of the line, Terra del Fuego.
- Length of stay is about 12 days on average for each species but length of stay can range from 1-40 days. It is quite variable but depends on mass of the bird at the time it is captured
- The pink line is from the 15 red knots added in. As birds get heavier, length of stay decreases. A 10% change in body mass per species results in an equivalent change in length of stay for each species
- Migration speed faster in spring than in fall, largely because of an increase stopover duration in fall.
- Migration speed faster in spring than in fall, largely because of an increase stopover duration in fall.
- Migration speed faster in spring than in fall, largely because of an increase stopover duration in fall.
- Surveys count what is present, and for animals that are on the move, this obvious fact leads to a variety of problematic biases. Many of these could be addressed by using tracking data to augment survey data.
- Surveys of migrant birds are often “efficient” because large numbers of birds concentrate (in space and time) at a restricted set of stopover locations. However, because they are moving through an area, their behaviour can influence whether or not they are present at the time of the survey. This can lead to two important sources of bias – length of stay bias and frame bias.
- Length of stay bias refers to the fact that length of stay at a location is directly related to the count. If the length of stay drops by half, the mean count will drop by half. This issue has been highlighted for shorebirds – rebounding populations of birds of prey could be reducing length of stay and leading in part to the observed declines in counts.
- Length of stay bias refers to the fact that length of stay at a location is directly related to the count. If the length of stay drops by half, the mean count will drop by half. This issue has been highlighted for shorebirds – rebounding populations of birds of prey could be reducing length of stay and leading in part to the observed declines in counts.
- Length of stay bias refers to the fact that length of stay at a location is directly related to the count. If the length of stay drops by half, the mean count will drop by half. This issue has been highlighted for shorebirds – rebounding populations of birds of prey could be reducing length of stay and leading in part to the observed declines in counts.
- Frame Bias refers to the fact that birds can move in and out of the set of surveyed sites. We often don’t know what fraction of the population is counted in each region, which birds are counted more than once, what fraction of the population never enters the sampling frame, and whether this fraction changes over time. These issues can lead to important biases, whereby regional trends are difficult to combine and it’s difficult to say with certainty that observed declines are real – might birds simply have moved out of the surveyed areas?
- The solution – is to tag a statistically rigorous sample of birds from the population and use tracking data from this sample to determine the time that birds remain in surveyed areas, and the fraction of the population the population passing through this sampling frame. With tracking data we can convert potentially biased “survey counts” to unbiased “population estimates”.
- BOEM telemetry array
- BOEM telemetry array