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  "author": null,
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  "code": "7b.b.yd",
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  "code": "7b.b.yd",
            
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  "contributor": "NIOZ Royal Netherlands Institute for Sea Research",
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  "contributor": "NIOZ Royal Netherlands Institute for Sea Research",
            
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  "creator_user_id": "20ff4b59-2dcf-4b58-8a9a-8805da8c9f5c",
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  "creator_user_id": "20ff4b59-2dcf-4b58-8a9a-8805da8c9f5c",
            
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  "creators": 
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  "creators": 
            
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me\":\"Lok\",\"orcid\":\"0000-0003-3753-8501\",\"affiliation\":\"Royal 
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me\":\"Lok\",\"orcid\":\"0000-0003-3753-8501\",\"affiliation\":\"Royal 
            
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Netherlands Institute for Sea 
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Netherlands Institute for Sea 
            
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pondingauthor\":true,\"contactemailaddress\":\"tamar.lok@nioz.nl\"}]",
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pondingauthor\":true,\"contactemailaddress\":\"tamar.lok@nioz.nl\"}]",
            
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  "dataset_persistent_id": "DOI:10.25850/nioz/7b.b.yd",
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  "dataset_persistent_id": "DOI:10.25850/nioz/7b.b.yd",
            
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  "deposit_date": "2023-01-12",
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  "deposit_date": "2023-01-12",
            
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  "depositor": "Tamar Lok",
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  "depositor": "Tamar Lok",
            
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  "distribution_date": "2023-01-12",
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  "distribution_date": "2023-01-12",
            
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  "distributor": "Research Data Management(NIOZ Royal Netherlands 
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  "distributor": "Research Data Management(NIOZ Royal Netherlands 
            
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Institute for Sea Research)",
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Institute for Sea Research)",
            
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  "doi_date_published": "2023-01-30",
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  "doi_date_published": "2023-01-30",
            
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  "funding_references": 
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  "funding_references": 
            
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\":\"WF209925\",\"awardtitle\":\"Metawad\",\"formatted\":\"Waddenfonds 
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\":\"WF209925\",\"awardtitle\":\"Metawad\",\"formatted\":\"Waddenfonds 
            
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- WF209925 - Metawad\"},{\"name\":\"Netherlands Organisation for 
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- WF209925 - Metawad\"},{\"name\":\"Netherlands Organisation for 
            
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Scientific Research 
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Scientific Research 
            
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(NWO)\",\"awardnumber\":\"016.Veni.192.245\",\"awardtitle\":\"Veni 
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(NWO)\",\"awardnumber\":\"016.Veni.192.245\",\"awardtitle\":\"Veni 
            
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grant Tamar Lok\",\"formatted\":\"Netherlands Organisation for 
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grant Tamar Lok\",\"formatted\":\"Netherlands Organisation for 
            
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Scientific Research (NWO) - 016.Veni.192.245 - Veni grant Tamar 
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Scientific Research (NWO) - 016.Veni.192.245 - Veni grant Tamar 
            
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Lok\"},{\"name\":\"Netherlands Organisation for Scientific Research 
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Lok\"},{\"name\":\"Netherlands Organisation for Scientific Research 
            
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(NWO)\",\"awardnumber\":\"Spinoza Premium 
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(NWO)\",\"awardnumber\":\"Spinoza Premium 
            
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2014\",\"awardtitle\":\"Spinoza Premium Theunis Piersma\"}]",
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2014\",\"awardtitle\":\"Spinoza Premium Theunis Piersma\"}]",
            
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  "name": "7bbyd",
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  "name": "7bbyd",
            
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  "notes": "Background\nQuantifying foraging success in space and time 
37
  "notes": "Background\nQuantifying foraging success in space and time 
            
38
and among individuals is essential for answering many\necological 
38
and among individuals is essential for answering many\necological 
            
39
questions and may guide conservation efforts. However, collecting this 
39
questions and may guide conservation efforts. However, collecting this 
            
40
information is challenging for\nspecies that forage on mobile prey and 
40
information is challenging for\nspecies that forage on mobile prey and 
            
41
are difficult to observe visually, for example, because they forage 
41
are difficult to observe visually, for example, because they forage 
            
42
in\ninaccessible areas or at night. In such cases, the use of tracking 
42
in\ninaccessible areas or at night. In such cases, the use of tracking 
            
43
devices that simultaneously collect location and\nacceleration data 
43
devices that simultaneously collect location and\nacceleration data 
            
44
may provide a solution if foraging success can be extracted 
44
may provide a solution if foraging success can be extracted 
            
45
successfully. The aim of this study\nwas to assess how well searching 
45
successfully. The aim of this study\nwas to assess how well searching 
            
46
for and ingesting prey, among other behaviours, could be distinguished 
46
for and ingesting prey, among other behaviours, could be distinguished 
            
47
from\n20 Hz acceleration data collected by GPS/ACC-trackers mounted on 
47
from\n20 Hz acceleration data collected by GPS/ACC-trackers mounted on 
            
48
the back of Eurasian spoonbills Platalea\nleucorodia. Upon capturing a 
48
the back of Eurasian spoonbills Platalea\nleucorodia. Upon capturing a 
            
49
prey, spoonbills make a distinct movement with their head and back to 
49
prey, spoonbills make a distinct movement with their head and back to 
            
50
throw the\nprey from the tip of the bill into the 
50
throw the\nprey from the tip of the bill into the 
            
51
throat.\n\nMethods\nWe compared the behavioural classification 
51
throat.\n\nMethods\nWe compared the behavioural classification 
            
52
performance of random forest models that were trained and tested\non 
52
performance of random forest models that were trained and tested\non 
            
53
video-annotated acceleration data segments of different (fixed or 
53
video-annotated acceleration data segments of different (fixed or 
            
54
flexible) lengths. The best-performing\nmodel was then applied to 4 
54
flexible) lengths. The best-performing\nmodel was then applied to 4 
            
55
years of data of spoonbills foraging in the Wadden Sea during the 
55
years of data of spoonbills foraging in the Wadden Sea during the 
            
56
breeding\nseason, to explore seasonal and annual variation in prey 
56
breeding\nseason, to explore seasonal and annual variation in prey 
            
57
ingestion rates.\n\nResults\nHighest classification accuracies (as 
57
ingestion rates.\n\nResults\nHighest classification accuracies (as 
            
58
indicated by the F-measure, a balanced measure of precision 
58
indicated by the F-measure, a balanced measure of precision 
            
59
and\nsensitivity) of foraging behaviours were achieved by analysing 
59
and\nsensitivity) of foraging behaviours were achieved by analysing 
            
60
short fixed-length segments (0.4\u20130.8 s) 
60
short fixed-length segments (0.4\u20130.8 s) 
            
61
or\n\u201cflexibly-cut\u201d segments. The F-measure was very high (> 
61
or\n\u201cflexibly-cut\u201d segments. The F-measure was very high (> 
            
62
0.90) for searching, standing, sitting and flying\n(distinguishing 
62
0.90) for searching, standing, sitting and flying\n(distinguishing 
            
63
active and passive flight), 0.73 for ingesting prey and 0.65 for 
63
active and passive flight), 0.73 for ingesting prey and 0.65 for 
            
64
walking. False positive and\nnegative prey ingestions were equally 
64
walking. False positive and\nnegative prey ingestions were equally 
            
65
likely and most often confused with searching, resulting in a close 
65
likely and most often confused with searching, resulting in a close 
            
66
match\nbetween the predicted and observed prey ingestion rates. 
66
match\nbetween the predicted and observed prey ingestion rates. 
            
67
Application of the best-performing model revealed\nstrong seasonal 
67
Application of the best-performing model revealed\nstrong seasonal 
            
68
patterns in prey ingestion rates in the Wadden Sea that varied between 
68
patterns in prey ingestion rates in the Wadden Sea that varied between 
            
69
years.\n\nConclusions\nWe show that prey ingestion rates of Eurasian 
69
years.\n\nConclusions\nWe show that prey ingestion rates of Eurasian 
            
70
spoonbills can be fairly accurately estimated from acceleration\ndata. 
70
spoonbills can be fairly accurately estimated from acceleration\ndata. 
            
71
These results are promising for the use of spoonbills equipped with 
71
These results are promising for the use of spoonbills equipped with 
            
72
GPS/ACC-trackers as monitors of\nspatial and temporal variation in the 
72
GPS/ACC-trackers as monitors of\nspatial and temporal variation in the 
            
73
availability of small fish and shrimp, which is key to understand 
73
availability of small fish and shrimp, which is key to understand 
            
74
their\nforaging and migratory movements of spoonbills and provides 
74
their\nforaging and migratory movements of spoonbills and provides 
            
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information on the quality of (coastal) wetlands.",
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  ],
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  "title": "Data from: Prey ingestion rates revealed by back-mounted 
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  "title": "Data from: Prey ingestion rates revealed by back-mounted 
            
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  "version": "1"
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  "version": "1"
            
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}
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}