Table 1 Description and details of data used for the relative index of occurrence (RIO) in this study for two goose species. Subregions are shown in Fig. 1.

From: Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the ‘New Digital Arctic’

Species and sample size details

Location and subregion in Study Area

Survey focus

Source

Time period

Observer

Comment

(a) Training data

Anser albifrons (n = 219; Broods present = 142, Broods absent = 77; Non-breeders present = 95 Non-breeders absent = 124)

Yakutia

Brood & Non-breeders

Boat

2017, 2018

IB

 

Chaun

Brood & Non-breeders

Boat

2002 till 2019

DS, AK

 

Chukotka

Brood & Non-breeders

Aerial

2002,

AK

 

Chukotka: Koryak Highland

Brood & Non-breeders

Aerial

1997

AK

 

Anser fabalis (n = 593; Broods present = 213, Broods absent = 380; Non-breeders present = 303, Non-breeders absent = 290)

Yakutia

Brood & Non-breeders

Boat

2017, 2018

IB

 

Chaun

Brood & Non-breeders

Boat

2002 till 2019

DS, AK

 

Chukotka

Brood & Non-breeders

Aerial

2002,

AK

 

Chukotka: Koryak Highland

Brood & Non-breeders

Aerial

1997

AK

 

Species

Source

Match with predictive model

Comment

   

(b) Testing data

Anser albifrons

GBIF presence (n = 63)

Good

These data are ‘just’ occurrences but indicate presence absence in the landscape

   

Compiled literature presence absence (n = 14)

Good

These data are also ‘just’ presence/absence but carry some attributes on broods and non-breeders (not shown here). The source is from the literature and first-time presented as a GIS layer

   

Anser fabalis

GBIF presence (n = 17)

Good

These data are ‘just’ occurrences but indicate presence absence in the landscape

   

Compiled literature presence absence (n = 18)

Good

These data are also ‘just’ presence/absence but carry some attributes on broods and non-breeders (not shown here). The source is from the literature and first-time presented as a GIS layer