Update on Indicator work A&D
SEAL 12 Tallinn, Estonia
…and an update from harbour porpoise surveys in Germany
Update on Indicator work A&D and an update from harbour porpoise - - PowerPoint PPT Presentation
Update on Indicator work A&D and an update from harbour porpoise surveys in Germany SEAL 12 Tallinn, Estonia me of a coffe coffee infused drafting Out utcome ng session by the he A&D A&D indi dicator grou oup on n Tu Tues
Update on Indicator work A&D
SEAL 12 Tallinn, Estonia
…and an update from harbour porpoise surveys in Germany
Out utcome me of a coffe
ng session by the he A&D A&D indi dicator grou
n Tu Tues esday
1) 1) Prune ne the he old A&D A&D indi dicator and nd create a new ew indi dicator 2) 2) Abu bund ndance is is a l lar arge scale, low frequ quency, h high l lag indi dicator 3) 3) Tr Trends ds i in den ensity is is a sma mall scale, high gh frequ quency, , low lag g indi dicator
Abunda ndanc nce e Indica
As Assessment Un Unit it Sc Scale le 2
1. . Acous
ic s survey eys for t the B e Balt ltic ic proper
2. . DS / / Acous
ic fo for wester ern B n Balt ltic ic Se Sea 3. . poole
sub basins ins as as spat atial ial scale ale 4. . every ry 6 6 years rs
https://doi.org/10.1016/j.biocon.2018.06.031
Very obviously a SAMBAH Map
Carlén et al. 2018: Basin-scale distribution of harbour porpoises in the Baltic Sea provides basis for effective conservation actions. Biological Conservation, 226(June), 42–53.
Viquerat et al. 2014: Abundance
phocoena) in the western Baltic, Belt Seas and Kattegat. Marine Biology, 161(4). https://doi.org/10.1007/s00227
MiniSCANS
https://doi.org/10.1007/s00227-013-2374-6
https://synergy.st-andrews.ac.uk/scans3/
Block Density CV Abundance CL low CL high 1 1.33 0.472 31,249 6,111 159,786 2 1.04 0.304 42,324 23,368 76,658 Total 1.15 0.285 73,573 39,383 137,443
Trends in density and distributi
Wi Will i ind ndicat ate shor short t ter erm changes changes at at a a loca
scale Will l pr provi
nfor
ation
dist stribu bution
fts with ithin in popul populat ation bor border ders Will l com commit count countries es to to under undertak ake moni
ng effo fforts ts
The new Indicator
Will be be based on based on densi density / change change in n densi density at at cr critical si sites es Will ll i identify ify critic ical s l site tes based on based on exper expert opi
Whi hich can h can al also be
bot bottlen enec ecks et etc. c.
The new Indicator
Bedeutung für zukünftige internationale Monitoringbestrebungen
Moni
ng Germany
Survey areas 2002 - 2016
Area Abundance [Animals] Density [Animals /km²] Average group size [Animals/ group] CV Effort [km] Total 3,834 (2,237 – 6,796) 0.2303 (0.1344 – 0.4082) 1.12 0.2779 2,457 E 820 (257 – 1,750) 0.1738 (0.0545 – 0.3708) 1.16 0.4390 745 FE 620 (323 – 1,156) 0.2436 (0.1269 – 0.4545) 1.21 0.3417 411 FW 893 (347 – 1,916) 0.1904 (0.0741 – 0.4088) 1.17 0.4169 710 GW 1,501 (750 – 2,713) 0.3198 (0.1598 – 0.5778) 1.04 0.3176 592
Campaigns:
Summer Averages
https://geodienste.bfn.de/schweinswalverbreitung
Survey areas 2017 - 2021
I – westliche Ostsee (Kieler Förde) J – Fehmarn K – Pommersche Bucht West L – Pommersche Bucht Ost M – Greifswalder Bodden N – Oderbank
16.10.2018 19
19
Moni nitor toring ngGu
Line transect sampling
Line transect distance sampling
Sichtungen zum Transekt über Winkel α und konstante Flughöhe h
Linie
h d α
Detectionfunction
Distanzklassen # Sichtungen
w (Datenbeschnitt)
→ Variiert je nach
Bedingungen auf dem Transekt μ = effektive Streifenbreite
Estimating the abundance
v m m g g v v v
s n n L A N × + × = µ µ ˆ ˆ ˆ
Gesamtfläche des Untersuchungsgebiets Transektstrecke, die on effort beflogen wurde Anzahl der Sichtungen unter guten und moderaten Bedingungen effektive Streifenbreite μ für gute und moderate Bedingungen Mittlere beobachtete Gruppengröße
Tr Trends ends Bayes
Trending and bending
are going down in the German Baltic Sea
trend
Dichte
Trending and bending
Proper Bayesian analysis of an anonymous survey area in Germany, not yet finished (therefore anonymised)
Trending and bending
Kruschke JK, Liddell TM. The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon Bull Rev. 2017. doi: 10.3758/s13423-016-1221-4. PubMed PMID: 28176294.