A ision o pa icipa o y models o animal
mo emen : a case s udy wi h Moose⋆
Jugal Pa el1,3and Niiyokamigaabaw Deond e Smiles2,3
1Depa men o Geog aphy, McGill Uni e si y, Mon eal, Quebec
[email p o ec ed]
2Ins i u e o Resou ces, En i onmen , and Sus ainabili y, Uni e si y o B i ish
Columbia, Vancou e , B i ish Columbia
[email p o ec ed]
3Geog aphic Indigenous Fu u es Collabo a o y
Abs ac . We en ision an indigenous geog aphic app oach o co-modeling
animal mo emen in igh ly coupled socioecological sys ems. This pa-
pe ou lines ou ision o a mo emen -place model o animal mo e-
men . Applicable o coupled sys ems, his mixed-me hods app oach p i-
o i izes si ua ed knowledge and da a so e eign y. Ou ision equi es
h ee mo emen - ocused modelling componen s: mo emen - ace, mo emen -
space, and mo emen -place. Toge he wi h communi y membe s, we en-
cou age i e a ion h ough each componen , while making dis inc ions o
da a so e eign y along he way.
We ou line a GeoAI app oach, which add esses conce ns ela ed o da a
a ailabili y and da a so e eign y, o en exp essed by people li ing wi hin
s udy sys ems. Fi s , his me hod ope a es on he p esump ion ha local
animal ajec o y da a is una ailable. Lack o animal ajec o y da a is
common ac oss socioecological sys ems, and in some cases collec ing new
da a is discou aged by people li ing wi hin coupled s udy sys ems; pos-
ing an in e es ing geospa ial da a challenge. Second, he app oach p io -
i izes da a so e eign y o communi y-held si ua ed knowledge by ou lin-
ing impo an dis inc ions be ween mo emen -space and mo emen -place
modelling componen s. Tha is, whe he a model inco po a es si ua ed
knowledge o no . In ou wo k, aces a e modelled using moose (Alces
alces) mo emen da a om h ee sou ce si es; hen aces a e ela ed o
en i onmen al spaces; which oge he o m he basis upon which we ini-
ia e mo emen -place co-modelling wi h local s akeholde s, bands, and
ibes ac oss Minneso a and no he n On a io.
By in ol ing people embedded wi hin s udy sys ems, ou ision o a
mo emen place model can be ealized by co-de eloping a spa ially-
explici and locally en iched agen -based model o a coupled socioeco-
logical sys em. Mo emen place models - models which a e co-de eloped
o in eg a e local si ua ed knowledge in o da a-d i en ep esen a ions o
mo emen - aim o enable o o he wise enhance socioecological esilience
by imp o ing how local policy decisions a e made (i.e., ei he wi h o
wi hou people li ing wi hin said sys ems; ei he wi h o wi hou impo -
an socioecological ela ions and in e ac ions being conside ed).
⋆DOI: h ps://doi.o g/10.5281/zenodo.17686018
2 J. Pa el e al.
Keywo ds: GIScience ·Indigenous Geog aphy ·agen -based modelling
·animal mo emen
1 Vision
We en ision a mo emen -place model o animal mo emen o igh ly coupled
socioecological sys ems, which inco po a es and ex ends no ions o mo emen
aces and spaces ound in compu a ional mo emen analysis li e a u e. He e,
ajec o ies a e unde s ood as mo emen aces occu ing in a gi en en i onmen-
al space [1] [2] [3]. Ex ending his, we in oduce mo emen -place as an addi ional
aspec ocused on explici ly conside ing si ua ed knowledge o people embedded
wi hin coupled s udy sys ems.
In his ision pape , we desc ibe how we a e app oaching pa icipa o y agen -
based modeling o moose (Alces alces) ecology ac oss Minneso a and no he n
On a io. By combining compu a ional mo emen analysis wi h pa icipa o y
mapping and so wa e enginee ing p inciples, he me hod o e s a means o
communi ies o de elop policy, scien i ic geospa ial isualiza ions, and insigh as
hey see i . The en isioned h ee componen me hod – ace, space, and place
– is i e a i e, and in ended o enhance local decision-making ela ed o animal
mo emen . To emphasize da a so e eign y, mo emen ace and space aspec s o
modelling animal mo emen a e dis inguished om mo emen -place, in pa , by
p i acy, consen , and communi y-de e mined objec i es.
The emainde o his sec ion is o ganized along hese h ee mo emen mod-
elling componen s: mo emen aces, spaces, and places; and is ollowed by b ie
backg ound on ela ed concep s be o e concluding wi h a summa y o he en i-
sioned mo emen -place model and app oach o co-modelling animal mo emen
in coupled socioecological sys ems.
1.1 Mo emen aces
Mo emen aces, in his case s udy, a e ep esen a ions o moose mo emen
ac oss h ee sou ce si es: 1. he Albe a-BC bo de no h o P ince Rupe [4]; 2.
nea Fo McMu ay [5]; and 3. he Uppe Koyukuk Ri e in Alaska [6]. These
da a a e a ailable ia Mo eBank - an open access eposi o y o animal mo e-
men da a, and we use hese o de elop a gene al moose mo emen model [7]. To
s a , we p ocess ajec o ies using Mo ingPandas [8]. We hen i Con inuous
Time Co ela ed Random Walks (CTCRW) o each indi idual [9]. CTCRWs
o e a dis inc ad an age: he capaci y o model uni o mly sampled ajec o ies,
using non-uni o mly sampled inpu ajec o ies [9]. Gene a ed CTCRWs o m
he mo emen - ace componen o modelling moose ecology in coupled sys ems
ac oss Minneso a and no he n On a io. Simul aneously, a p elimina y spa ial
agen -based model is p epa ed wi h ’moose-agen s’ ha use CTCRW o model
agen mo emen in simula ed spaces.
Fo he pu pose o ou ision, i is no s ic ly necessa y o use CTCRWs o
model mo emen aces. Any wo k low which esul s in ype II egula ajec o-
A ision o pa icipa o y models o animal mo emen 3
ies is encou aged o main ain simplici y in communica ion, collabo a ion, and
downs eam co-de elopmen o spa ial agen -based models.
1.2 Mo emen spaces
To demons a e de elopmen o a mo emen space model, we ela e ace ob-
jec s o common en i onmen al ea u es. We conduc in o mal in e iews and
ini ia e con e sa ion wi h biologis s and moose specialis s o help deciphe e-
gional en i onmen al a iables o o he spa ial ea u es hough o be a ec ing
moose beha iou . Thus a we ha e collec ed oad and ail ne wo k da a om
OpenS ee Map, and indices o an h opogenic hea lux (1KM esolu ion [10]),
p ecipi a ion, and ee co e p ocessed and a ailed by Google Ea h Engine. Ad-
di ional ele an en i onmen al ea u es may be iden i ied by he communi y a
a la e da e. This in o ma ion is hen o e laid wi h mo emen aces o ex ac
alues along mo emen aces. Using hese en i onmen ally-en iched mo emen
aces, we ain a andom o es classi ie on pa h segmen a ion labels. We apply
a simple h eshold o >2m/s o de ine mo ing beha iou s. We agg ega e ou pu s
om he andom o es classi ie , de eloping a mo emen selec ion su ace [11].
The moose agen based model is adap ed o inco po a e ou mo emen -selec ion
su ace, selec ing poin s mos likely o sui mo emen beha iou s.
A a ie y o me hods can be deployed o de elop beha iou selec ion su aces.
These a e simply ou pu s o esou ce, pa h, o beha iou selec ion me hods [12],
[13]. Howe e , he me hod mus be compa ible (i.e., able o in eg a e) wi h down-
s eam pa icipa o y mapping ou pu s. These may include digi iza ions o d awn
pa hs, ough polygons wi h unce ain placemen in space and ime, emo ional
assessmen s o places, o a wide a ie y o no commonly modeled spa ial ea u es
[14] [15]. These equi e explici in eg a ion when co-de eloping he mo emen -
place model.
Al hough in eg a ion in his en isioned con ex is ul ima ely quan i a i e
and compu a ional, agen -based models a e unique echnologies well posi ioned
o asc ibe simula ed objec s and spaces a a ie y o mu able a ibu es, each
wi h po en ial o be explici ly conside ed du ing simula ion. O e all, p ac i ion-
e s should p epa e hei me hodological app oaches o explici in eg a ion o
si ua ed knowledge. Ou deployed mo emen -space me hod can be adap ed o
include new spa ial ea u es as de e mined by he communi y [11] [16].
Gi en he abo e, we ini ia e he place aspec o modelling mo emen in cou-
pled sys ems. We p esen ou indings and gene alized mo emen ace and space
models o local s akeholde s, bands, and ibes ac oss Minneso a and no he n
On a io ha ha e po en ial in e es in co-de eloping a simula ion o moose ecol-
ogy.
1.3 Mo emen places
Ou mo emen ace and mo emen space modelling componen s ha e con-
ibu ed o a p elimina y and baseline spa ial agen -based model o moose ecol-
ogy. The nex s ep, mo emen -place modelling, is ocused on de ining agen -
4 J. Pa el e al.
based modelling objec i es and in eg a ing si ua ed knowledge, oge he wi h
communi y membe s.
Communi y membe s will be encou aged o i e a e h ough mo emen model-
ing componen s (i.e., ace, space, place), iden i ying ele an ea u es o socioe-
cological p ac ices (e.g., seasonali y, hun ing, ha es , ca e e c.,). Changes made
(e.g., new ea u es being iden i ied) a e in eg a ed in o a communi y held and
main ained mo emen -place moose agen -based model. This communi y held
model is essen ially (and li e ally) a o k o a public ‘mo emen -space’ model
eposi o y plus local changes. Fo each i e a ion, du ing he mo emen -place
modelling s ep, esea ch p ac i ione s should pose he ques ion: Should hese
changes be sha ed publicly? I he answe is no, o a gi en change, i is exclu-
si ely in eg a ed (i.e., pushed) in o he communi y-held mo emen -place model.
I i can be sha ed, he communi y may op o help in eg a e hei changes in o
a esea che -held mo emen -space model.
In mos espec s, he abo e is no enough in o ma ion o adequa ely model
animal mo emen s in an un ained o unseen a ge des ina ion (i.e., ha ing
dispa a e sou ce and a ge si es). Howe e , in he places we en ision ou ap-
p oach o (i.e., coupled socioecological sys ems) people hold si ua ed knowledge
o moose ela ions, beha iou , ecology, and en i onmen [17]. Ou app oach asks:
Can we de elop an adequa e simula ion o a moose socioecological sys em by
combining a gene alized mo emen model ( ained on un ela ed sou ce si es)
wi h si ua ed knowledge o local pa icipan s. To cla i y, he gene alized mo e-
men model is based on he CTCRW desc ibed abo e in ’Mo emen aces’, and
he mo emen -selec ion su ace desc ibed in ’Mo emen spaces’. While hei e-
sul ing in eg a ion in o an agen -based model o ms he communi y-held mo emen -
place model.
Fig. 1. Wo k low o a mo emen -place model, ollowing h ee mo emen modelling
componen s - ace, space, and place.
A ision o pa icipa o y models o animal mo emen 5
1.4 Mo emen -place Model
We combine compu a ional mo emen analysis wi h pa icipa o y so wa e en-
ginee ing and pa icipa o y mapping me hods o co-de elop animal mo emen
models wi h communi ies embedded wi hin coupled s udy sys ems. In his con-
ex (i.e., igh ly coupled socioecological sys ems), we belie e GeoAI and com-
plex sys ems app oaches may enable a way o: i s gene alize a moose mo emen
model; hen apply, in collabo a ion wi h si ua ed knowledge holde s and commu-
ni y membe s, in o ma ion in o a spa ial agen -based model. The ou pu s o such
a model a e geo- isual, easy- o-unde s and, and can be powe ul pa icipa o y
models, use ul o in o ming local en i onmen al policy [18] [19].
Ou app oach is p emised upon he unde s anding ha people embedded
wi hin socio-ecological complex adap i e sys ems a e be e equipped o in e-
g a e in o ma ion ega ding hei own ela ions wi h land, animals, e c., in o
ecological models [17]. Wi h wo ou comes, helping in o m mo e e icacious en-
i onmen al policy, and de eloping a means o p ese e socio-ecological ela-
ions. By de ini ion, he be e socio-ecological ela ions a e main ained, he
mo e esilien a coupled sys em can be o en i onmen al dis up ions (e.g., cli-
ma e change, apid an h opogenic de elopmen , e c.). The adap i e capaci y o
socio-ecological sys ems, ha is he abili y o main ain c i ical in o ma ion lows,
a e pa icula ly ele an o a oid global ecosys em collapse and a ious ela ed
ca as ophes [20] [21] [22] [23].
Collec ing new animal mo emen da a can be esou ce in ensi e. Simila ly,
communi ies may be unwilling o o he wise incapable o collec ing ajec o y
da a on animals in hei en i onmen . O en in igh ly coupled socioecologi-
cal sys ems, peoples embedded in s udy sys ems discou age animal moni o ing.
These si ua ions p o ide oppo uni ies o exci ing inno a ions in GIScience and
GeoAI o sol e such socioecological p oblems [24].
1.5 Indigenous Places
As esea che s who wo k as pa o a collec i e ha has buil ela ionships wi h
Indigenous communi ies and o ganiza ions [16], we emphasize he impo ance
o ensu ing ha his p oposed ision adhe es o es ablished bes p ac ices o
Indigenous da a so e eign y and meaning ul Indigenous pa icipa ion in he wo k
being done.
Al hough his o ically, geospa ial wo k wi h Indigenous communi ies has un
he isk o being ex ac i e in scope and p ac ice, wi h no bene i o da a e-
u ning o communi ies [25], con empo aneous bes p ac ices o pa icipa o y
wo k demand a he ba e minimum ac i e collabo a ion and pa icipa ion by
Indigenous communi ies, and he adhe ence by esea che s o key amewo ks
o e hical esea ch, such as CARE (collec i e bene i , au ho i y o con ol, e-
sponsibili y, and e hics) and he P inciples o OCAP (owne ship, con ol, access,
possession) [26] [27] [28] [29].
Ou p oposed me hodology ope a es unde he assump ion ha all da a ha
is collec ed wi h Indigenous communi ies belong o hose communi ies. Once
6 J. Pa el e al.
mo emen -place modelling is ini ia ed, he communi y has ull inpu and o e -
sigh o e he wo k done, and main ains da a so e eign y. Addi ionally, he model
we en ision in his pape is i e a i e, meaning we assume he e will be con e -
sa ions wi h communi ies abou he na u e o modelling, and how communi y
inpu s and wo ld iews can be placed a he cen e o he wo k. We iew he
communi y’s pa icipa ion as a amewo k h ough which models will change,
adap ing o local needs [30]. This means ha he model i sel becomes ied o
he communi y, and mul iple mo emen -place models may o igina e om a gen-
e alized animal mo emen model. While his a ec s ep oducibili y, he lack o a
eady s and-alone ep oducible wo k low upholds Indigenous communi y-based
esea ch da a so e eign y; in ha communi y inpu is a c i ical pa o he model,
and wi hou which he model canno meaning ully simula e local con ex .
2 Backg ound
The emainde o his pape sha es backg ound on key backg ound opics: Pa -
icipa o y GIScience and Agen -based Modelling Animal Mo emen be o e con-
cluding wi h a summa y o ou app oach and he en isioned ’mo emen -place’
model.
2.1 Pa icipa o y GIScience
Pa icipa o y echniques o e an al e na i e app oach o in o ming policy: col-
labo a i ely wi h communi ies. By co-de eloping mo emen models wi h local
s akeholde s o communi y membe s, pa icipa o y mo emen models o e a
means o dis up how insigh om compu a ional mo emen analysis is ope a-
ionalized.
Popula s a is ical echniques o modeling animal mo emen , esou ce se-
lec ion me hods, ha e demons a ed imp o ed accu acy when in eg a ed wi h
adi ional o local ecological knowledge [31]. Like selec ion me hods, ABMs a e
o en calib a ed using expe opinion. Fo bo h echniques people li ing wi hin
s udy sys ems can be e ep esen hei socio-ecological ela ions, enabling im-
p o ed compu a ional models o mo emen a , as Buchhol z e al., no es, local
scales [31].
Ramana h and Gilbe sugges echniques o e ec i e pa icipa o y agen -
based modelling d awing on so wa e enginee ing li e a u e [32]. Fila o a, Ve -
bu g, Pa ke , and S anna d ou line challenges o agen -based modelling socio-
ecological sys ems; highligh ing design, alida ion, spa ial ep esen a ion, and
in eg a ion wi h exis ing heo e ical models as key a eas o u u e con ibu-
ions [33]. C ooks, Cas le, and Ba y ou line se en challenges o agen -based
modelling complex adap i e spa ial sys ems, including alida ion, de ining he
pu pose o he model, and he ex en o which independen heo y in o ms model
speci ica ions and pa ame iza ion [34]. Ou app oach conside s hese eme ging
me hodological ends in agen -based models, and en isions co-de eloping and
co-modelling simula ions o socio-ecological sys ems using locally alid si ua ed
A ision o pa icipa o y models o animal mo emen 7
knowledge, using pa icipa o y so wa e enginee ing p inciples o de elop spa ial
agen -based models o animal mo emen .
2.2 Agen -based Modelling Animal Mo emen
Agen o indi idual based models (ABMs) a e objec -o ien ed p og amming
echniques used in social and ecological sciences o simula e and link ou comes
wi h policy, beha iou , o o he inpu c i e ia [35]. They can also be co-designed
wi h communi ies, e-o ien ing he pu pose and ou pu s o pa icipa o y agen -
based models o align wi h local objec i es, alues, and knowledge sys ems [18].
Agen -based app oaches o modelling mo emen a e pa icula ly ele an o
animals oaming la ge dis ances each day, o en passing h ough mul iple liminal
socioecological spaces [36] [37] and o balancing animal conse a ion and hu-
man li elihood in coupled socioecological sys ems [38] [39]. The simula ed space
an animal-agen mo es wi hin can be geog aphically explici , making spa ial
ABMs well-sui ed o isually ep esen and simula e ou comes ela ed o animal
mo emen [40] [41]. By p og amming au onomous objec s wi hin a model o
in e ac , simula ion app oaches enable obse a ion and expe imen a ion o how
in o ma ion may beha e in dynamic sys ems [42].
3 Conclusion
We build upon es ablished ideas o mo emen aces and spaces by in oducing
mo emen -place models o igh ly coupled socioecological sys ems. When people
embedded in coupled sys ems a e willing, in e es ed in, and able o in eg a e hei
si ua ed knowledge in o gene alized models o animal mo emen , mo e e icacious
and e hical en i onmen al policy can be de eloped. This ision pape ou lines
his app oach in ou wo k hus a wi h bands and Indigenous g oups ac oss
Minneso a and no he n On a io.
In compa ison o adi ional mo emen ecology me hods (e.g., adio eleme-
y, GPS colla s, e c.), ou app oach has a numbe o impo an ad an ages: 1.
i is less esou ce in ensi e, equi ing no new local moni o ing p ocedu es be se
up; 2. da a so e eign y emains unambiguously wi h he local communi y; and 3.
he me hod explici ly inco po a es si ua ed knowledge. The e a e also disad an-
ages: 1. gene alized models a e usually no applicable o new egions o animal
g oups and he e o e will ace esis ance om ad oca es o collec ing mo e local
animal mo emen da a; and 2. he me hod is dependen upon adi ional animal
moni o ing p ac ices; i no he e, elsewhe e o help de elop he ini ial gene alized
mo emen model.
Wi hou explici conside a ions o socioecological ela ions, we canno con-
se e dynamic and complex coupled sys ems. Mo emen -place models o e a
heo e ical app oach o inco po a ing si ua ed knowledge; a e c i ical and imely
gi en en i onmen al dis up ion and a looming c isis in (socio-)ecological e-
silience; and a e ele an as sys ems app oaches enjoy a enewed emphasis in
GIScience o educa ion [43].
8 J. Pa el e al.
We hope his ision pape enables u he discussion on he opics o In-
digenous Geog aphies, igh ly coupled socioecological sys ems, GIScience, and
how hey ela e o modelling animal mo emen in sys ems balancing human and
animal in e es s.
Disclosu e o In e es s. The au ho s ha e no compe ing in e es s o decla e ha
a e ele an o he con en o his a icle.
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