Mukeshkuma Bhenda ka
PhD Thesis 2025
Ad ancing en i onmen al DNA
app oaches o op imizing
aqua ic ecosys em moni o ing
and ecological assessmen
Supe iso
Naia a Rod íguez-Ezpele a
PhD Thesis
Ad ancing en i onmen al DNA app oaches o
op imizing aqua ic ecosys em moni o ing and
ecological assessmen
P esen ed by
Mukeshkuma Pa as am Bhenda ka
Thesis supe iso
Naia a Rod íguez-Ezpele a
Depa men
Zoology and Animal Cell Biology
PhD P og am
Ma ine En i onmen and Resou ces
Ap il 2025
(cc) 2025 Mukeshkuma Bhenda ka (cc by-nc-nd 4.0)
i
The esea ch ca ied ou in his Philosophiae Doc o hesis has been de eloped in AZTI -BRTA (Suka ie a,
Spain). Mukeshkuma Pa as am Bhenda ka has been suppo ed by Indian Council o Ag icul u al
Resea ch (ICAR) h ough he o his doc o al esea ch.
The esea ch wo ks has been unded by he INTERREG A lan ic A ea -
(EAPA_18/2018), by he Depa men o Economic De elopmen and In as uc u e o he Basque
- De elopmen and applica ion o gene ic me hods o imp o e
h p ojec
-
(CTM2017-89500-R), by he Game & Wildli e Conse a ion T us , Queen Ma y Uni e si y (QMUL) o
, by he Basque Wa e Agency (URA) h ough a con en ion
wi h AZTI, by he Eu opean Union's Ho izon Eu ope p og am (p ojec s GES4SEAS wi h g an ag eemen
no. 101059877 and OBAMA-NEXT wi h g an ag eemen no. 101081642).
Recommended ci a ion:
Bhenda ka , M. (2025). Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em
moni o ing and ecological assessmen . PhD Thesis. Depa men o Zoology and Animal Cell
Biology, Uni e si y o he Basque Coun y.
Co e page designed by he au ho .
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
ACKNOWLEDGEMENTS .......................................................................................................................
GENERAL INTRODUCTION ................................................................................................................. 2
1. The signi icance o aqua ic ecosys ems ......................................................................................... 3
1.1 Ecological unc ions and se ices ............................................................................................. 3
1.2 Fish as in ecological indica o s o aqua ic ecosys ems ............................................................. 5
1.3 The Economic Signi icance o Fish .......................................................................................... 5
1.4 Th ea s o ish biodi e si y and ishe ies sus ainabili y ............................................................ 6
2. The impo ance o ish biodi e si y moni o ing in aqua ic ecosys ems ..................................... 9
2.1 Cu en adi ional ish moni o ing me hods ............................................................................ 9
2.2 En i onmen al DNA (eDNA) analysis: a e olu iona y app oach o ish moni o ing and
ecological assessmen ......................................................................................................................... 11
3. Ra ionale o he s udy ................................................................................................................... 13
4. Hypo hesis, aim and objec i e ..................................................................................................... 13
4.1 Wo king hypo hesis ................................................................................................................ 13
4.2 O e a ching aim and objec i es ............................................................................................. 13
5. S uc u e o he Thesis ................................................................................................................. 14
CHAPTER 1 ............................................................................................................................................. 16
EXPLORING UNCHARTED TERRITORY: NEW FRONTIERS IN ENVIRONMENTAL DNA
FOR TROPICAL FISHERIES MANAGEMENT
Abs ac ................................................................................................................................................. 17
1. In oduc ion .................................................................................................................................. 18
2. Pe spec i es ................................................................................................................................... 20
2.1 Wha is eDNA and how is i analyzed? .................................................................................. 20
3. eDNA: a game change o opical ishe ies s udies? .............................................................. 22
3.1 Biomoni o ing and conse a ion ............................................................................................. 23
3.2 Fish mig a ion pa e ns ........................................................................................................... 25
3.3 Rep oduc i e s a us ................................................................................................................ 26
3.4 Sys ema ic de ec ion o a - isk, a e, o c yp ic species .......................................................... 27
3.5 Ea ly-wa ning sys em o in asi e and alien species ............................................................... 28
3.6 In e play o die s and opic in e ac ion .................................................................................. 29
3.7 Popula ion gene ics and eDNA ............................................................................................... 29
3.8 Na u al sample s DNA (nsDNA) ............................................................................................ 30
3.9 Addi ional applica ions o eDNA in he ishe ies sec o ........................................................ 31
4. Challenges and limi a ions o eDNA ........................................................................................... 32
4.1 Ba code e e ence lib a ies ..................................................................................................... 32
4.2 Abundance es ima ion ............................................................................................................ 34
4.3 Li e s ages ............................................................................................................................... 35
4.4 Unce ain y abou he ecology o eDNA ................................................................................ 35
4.5 S anda diza ion o me hods .................................................................................................... 36
5. Wha lies ahead o opical ishe ies and ecology using eDNA? ............................................. 37
6. Conclusions ................................................................................................................................... 38
CHAPTER 2 ............................................................................................................................................. 41
LESSONS LEARNED FROM APPLYING EDNA SURVEYING TO DIADROMOUS FISH
DETECTION ACROSS THE NORTH-EAST ATLANTIC REGION
TABLE OF CONTENT
iii
Abs ac .................................................................................................................................................42
1. In oduc ion .................................................................................................................................. 43
2. Ma e ial and Me hods .................................................................................................................. 45
2.1 Sampling loca ion and e e ence da a se ............................................................................... 45
2.2 Wa e sample collec ion and DNA ex ac ion ........................................................................ 47
2.3 Species-speci ic de ec ion assay de elopmen ........................................................................ 47
2.4 Quan i a i e PCR (qPCR) analysis ......................................................................................... 48
2.5 Digi al PCR (dPCR) analysis ................................................................................................. 49
2.6 Quan i ica ion o dPCR and qPCR analysis ........................................................................... 50
2.7 Con usion ma ix analysis ...................................................................................................... 50
3. Resul s............................................................................................................................................ 51
3.1 Compa a i e pe o mance o eDNA analysis ......................................................................... 51
3.2 Ri e speci ic de ec ion a e ................................................................................................... 53
3.3 Insigh om digi al PCR (dPCR) and quan i a i e PCR (qPCR) assessmen ......................... 54
3.4 eDNA abundance pa e ns along i e s e ches ..................................................................... 55
4. Discussion ...................................................................................................................................... 57
4.1 De ec ion disc epancies among species .................................................................................. 57
4.2 When and how o sample ........................................................................................................ 58
4.3 Me hodological di e ences .................................................................................................... 59
4.4 Can eDNA be used as eliable sou ces o p esence/absence o diad omous ish? ................ 60
CHAPTER 3 ............................................................................................................................................. 63
ADVANCING ECOLOGICAL ASSESSMENT: THE INTEGRATION OF EDNA
METABARCODING INTO AN ESTUARINE FISH INDEX
Abs ac ................................................................................................................................................. 64
1. In oduc ion .................................................................................................................................. 65
2. Ma e ial and Me hods .................................................................................................................. 68
2.1 S udy a ea and sample collec ion ........................................................................................... 68
2.2 DNA ex ac ion and amplicon lib a y p epa a ion ................................................................. 68
2.3 Read p e-p ocessing and axonomic assignmen .................................................................... 69
2.4 AFI calcula ions ...................................................................................................................... 70
2.5 S a is ical analysis .................................................................................................................. 71
3. Resul s............................................................................................................................................ 72
3.1 Sampling e iciency o eDNA and bo om awling ............................................................... 72
3.2 Assessing awl and eDNA-based es ua ine ecological s a us ................................................ 73
4. Discussion ...................................................................................................................................... 76
4.1 Me hodological con as s ........................................................................................................ 76
4.2 Beyond he ne : eDNA edge in es ua ine ecological assessmen ............................................ 79
5. Way o wa d ................................................................................................................................. 80
GENERAL DISCUSSION ....................................................................................................................... 83
1. No jus ools - S a egies: Me hodological choices shape de ec ion......................................... 85
1.1 Assay sensi i i y and species de ec abili y ............................................................................. 85
1.2 Di e en ool, di e en u hs................................................................................................. 86
2. De ec ing he unde ec able: In e p e a ing alse signal in eDNA da a..................................... 87
2.1 False posi i es: con ex is e e y hing ..................................................................................... 88
2.2 Unco e ing alse nega i es ..................................................................................................... 88
3. Beyond species de ec ion .............................................................................................................. 89
3.1 opical ecosys ems ............................................................... 90
4. The big pic u e: ad ancing eDNA science o he u u e .......................................................... 91
4.1 Imp o e unde s anding o eDNA a e and anspo ............................................................... 92
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
4.2 Enhance he quan i a i e powe o eDNA ..............................................................................92
4.3 Expand and egionalize e e ence da abases .......................................................................... 92
4.4 In eg a e eDNA analysis in o policy and moni o ing amewo ks ......................................... 92
4.5 Adop au oma ion and emo e moni o ing echnologies ......................................................... 93
4.6 P omo e in e disciplina y and inclusi e collabo a ion............................................................ 93
4.7 Expand owa d ecosys em-le el, mul i- ophic eDNA assessmen s ....................................... 93
4.8 Ad ance Global S anda diza ion o eDNA Analysis .............................................................. 93
CONCLUSION AND THESIS ................................................................................................................ 95
REFERENCES ......................................................................................................................................... 98
Appendix A .............................................................................................................................................. i
Appendix B .......................................................................................................................................... xxii
ACKNOWLEDGEMENTS
Emba king on a PhD jou ney a om home has been one o he mos ans o ma i e expe iences o my li e. Coming
om India o Spain, his jou ney was no jus abou ea ning a deg ee i was abou g ow h, adap a ion, and cons an
lea ning. Fo me, mo e han he PhD i le i sel , i was he p ocess, he people, and he expe iences ha uly ma e ed.
Fi s and o emos , I would like o exp ess my deepes g a i ude o my supe iso . Some people may no explain
e e y hing in wo ds, ye hei p esence, au a, and pe sonali y become a silen ye powe ul guide. You ha e been one o
hose people eaching h ough example, leade ship, and cha ac e . Thank you o showing me he alue o quie
s eng h and hough ul p ecision.
To my esea ch g oup, I eel inc edibly lucky o ha e walked his pa h wi h such inspi ing colleagues and iends. C is ina,
a e me la e hose small ac s o kindness mean mo e han wo ds. O iol, you sha p insigh s and a en ion o
de ail we e like a double-edged swo d challenging me o imp o e while guiding me wi h p ecision. Inaki, he mas e o
he lab you hands-on suppo and pa ience helped me na iga e so many challenges. Alice, hank you o being a
mo i a o you ene gy and encou agemen kep me going. Specieal hanks o Ma ina, Na alia Díaz A ce, Na alia
Gu ie ez, Ike hank you o being pa o his jou ney and o you sugges ion ime o ime and wa m h. I would also
like o hank all he wonde ul people a AZTI who s ood by me h ough he highs and lows o e hese yea s. You
suppo , bo h pe sonal and p o essional, uly shaped my hinking and my expe ience. I am especially g a e ul o Lo ena,
Roge , Elsa, Xa i, Ma ía, Isa, Ane, Iosu, Ad i, and Uxue. A hea el hank you o Césa , o ensu ing I ne e lacked
any hing when i came o echnical suppo especially when dealing wi h o icial Indian websi es. You help was o en
he quie o ce ha kep hings unning smoo hly.
To my iends in Be meo e en hough you may no ha e ully known wha I was doing, hei suppo , iendship, and
company ga e me a sense o belonging. A hea el hanks o Kama an Bhai om Pakis an you wa m h and iendship
made me eel a home in a o eign land. You eminded me ha home is no always a place
I also wish o acknowledge he iends who we e he e when i ma e ed he mos Ka an, Yogesh, P amod, Heman ,
and Lohi h Si hank you o you cons an ele-suppo , mo i a ion, and iendship h oughou he ups and downs o
his PhD.
I ex end my since e g a i ude o he hen Di ec o o my ins i u e, and o he Di ec o Gene al, ICAR, D . Pa hak Si , o
making my in e na ional esea ch isi possible. My hea el hanks o Bhaska Si , Pawa Si , Ku ade Si , Ni male Si ,
Kakade Si , and P ashan Si scien is s om ICAR-NIASM, Ba ama i who s ood by e e y s ep o he way and
suppo ed me in adminis a i e wo k om India.
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
I would also like o acknowledge he Indian Council o Ag icul u al Resea ch (ICAR) o unding his PhD.
hank ul o he adminis a i e s a a ICAR-NIASM, Ba ama i, o hei pa ience, coope a ion, and suppo h oughou
he p ocess.
To my big amily back home hank you o you cons an encou agemen , p aye s, and belie in me. You lo e has
been a silen s eng h du ing he oughes days. To my mo he you endless lo e, sac i ices, and unwa e ing suppo
ha e been he And inally, o my wi e and son you
we e my ancho du ing his jou ney. Thank you o you lo e, pa ience, and sac i ices. You unde s anding du ing he
long hou s, you encou agemen when I doub ed mysel , and you p esence kep me going. Ishaan, you innocen
smiles ga e me hope on he ha des days. This accomplishmen is as much you s as i is mine.
This PhD was ne e jus abou academic achie emen . I was a lesson in esilience, humili y, and abo e all, human
connec ion. Thank you all o being a pa o i .
This hesis is dedica ed o my mo he
1
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
8
s esso s ha can be le hal o sub-le hal o ish. Indus ial e luen s, ag icul u al uno
laden wi h e ilize s and pes icides, sewage, and plas ics all con ibu e o he pollu ion
bu den in wa e ways. In many egions, basic was ewa e ea men is lacking mo e han
80% o global was ewa e is discha ged un ea ed in o i e s o oceans (UNESCO, 2017).
mos ma ine li e, and o e 400 such hypoxic zones ha e been epo ed wo ldwide (Diaz
& Rosenbe g, 2008).
Unsus ainable ishing emains a c i ical h ea o bo h ma ine and eshwa e ish
species. Ad ances in ishing echnology and e o ha e led o he deple ion o many
a ge species and conside able byca ch ( he unin en ional cap u e o non- a ge species,
including ju eniles and endange ed species). Cu en ly, 37.7% o global ish s ocks a e
exploi ed beyond biologically sus ainable le els (FAO, 2024). Many comme cially
signi ican species, such as una and cod, ha e su e ed d ama ic popula ion declines,
dis up ing ma ine ecosys ems and global ishe ies. In inland wa e s, o e ha es ing ish
( o ood, aqua ium ade, o bai ) has d i en some species o a i y o ex inc ion,
e
a ge ed species; i can al e communi y s uc u e and ecosys em unc ion. The emo al
o la ge p eda o y ish can cause mesop eda o elease (smalle ish and in e eb a es
inc ease, po en ially o e g azing habi a ), while he loss o he bi o ous ish on co al ee s
con ibu es o algal o e g ow h and ee decline (McCauley e al., 2010).
The in oduc ion o non-na i e species in o aqua ic ecosys ems can dis up na i e
ish popula ions h ough p eda ion, compe i ion, o disease. In asi e p eda o s o
compe i o s may ou compe e na i e ish o ood o habi a , o en because he na i es
ha e no e ol ed de enses agains hem. Nea ly 33% o eshwa e ish ex inc ions in he
pas cen u y ha e been a ibu ed o in asi e species (IUCN, 2023).
Among hese h ea s, clima e change poses a pe asi e and g owing h ea o ish
biodi e si y ac oss he globe (Pigo e al., 2023). Wa ming wa e empe a u es, shi ing
p ecipi a ion pa e ns, and mo e equen ex eme e en s (d ough s, loods, s o ms) a e
al eady impac ing aqua ic ecosys ems p o oundly. Many ish a e sensi i e o empe a u e,
elying on speci ic he mal anges o op imal g ow h and ep oduc ion. As wa e s wa m,
species a e being pushed ou o hei his o ical anges s udies ha e documen ed
GENERAL INTRODUCTION
9
polewa d and dep h ange shi s o nume ous ma ine ish a an a e age a e o ens o
kilome e s pe decade as hey ack coole habi a s (Pinsky e al., 2013). Some species
bene i om wa ming and expand, while o he s decline o a e o ced in o sh inking
e ugia. Addi ionally, 17% o h ea ened eshwa e ish species a e di ec ly a ec ed by
clima e change, expe iencing habi a loss due o dec easing wa e le els, ising sea le els
pushing seawa e in o i e s, and shi ing seasonal pa e ns (IUCN, 2023). Faced wi h his
con luence o p essu es, ish popula ions se e as sen inels o ecosys em change and hei
moni o ing is c ucial o sa egua ding aqua ic ecosys em.
2. The impo ance o ish biodi e si y moni o ing in
aqua ic ecosys ems
Gi en he widesp ead h ea s o aqua ic ecosys ems, moni o ing ish biodi e si y
is c i ically impo an o unde s anding ecosys em heal h, de ec ing eme ging p oblems,
and guiding conse a ion e o s (B ode sen & Seehausen, 2014). Fish a e o en one o
he i s g oups o espond o en i onmen al change declines in sensi i e ish species o
shi s in communi y composi ion can se e as an ea ly indica o o ecological
dis u bances, including declining wa e quali y, habi a deg ada ion, and clima e-d i en
shi s (Okwuosa e al., 2019). Moni o ing in his con ex means sys ema ically su eying
ish species p esence, abundance, and demog aphics in each habi a o e ime. Such da a
allows us o es ablish baselines, de ec de ia ions, and assess he ou comes o
managemen in e en ions.
2.1 Cu en adi ional ish moni o ing me hods
Humans ha e long moni o ed and managed ish popula ions using a a ie y o
adi ional su ey me hods, each de eloped o obse e o sample ish in di e en habi a s.
These con en ional echniques ha e p o ided in aluable da a o ishe ies managemen
and ecological esea ch (Fig 2). These app oaches encompass a ious echniques, each
wi h dis inc ad an ages and limi a ions. Visual su eys, such as sno keling and di ing,
allow di ec obse a ion o ish species, abundance, and beha io bu a e o en limi ed by
wa e cla i y and species iden i ica ion challenges (Thu ow e al., 2012). A a ie y o ne s
a e employed o cap u e ish o moni o ing, including gill ne s, seine ne s, and awl ne s,
o cap u e ish o popula ion s udies. Gill ne s a e se s a iona y in he wa e ; ish ha
a emp o swim h ough become en angled by hei gills. Seine ne s a e la ge mesh
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
10
cu ains ha in es iga o s d ag h ough shallow wa e o enclose an a ea o he d ish in o
he ne . T awl ne s a e owed behind boa s (e.g., bo om awls along he sea loo , o mid-
wa e awls) o sample ish o e la ge a eas in open wa e o ben hic habi a s. Each
ne ing echnique, howe e , has biases o ins ance, gill ne s migh miss e y small o
e y la ge ish, and awls may no wo k well in s uc u ally complex habi a s ( ee s, weed
beds) whe e ne s would snag. Impo an ly, ne ing is in asi e and can be non-selec i e:
i o en cap u es non- a ge species (byca ch) and can inju e o kill he ish caugh
(Balasch & To , 2019). In eshwa e sys ems, elec o ishing is a s anda d me hod o
su eying ish, especially in s eams and i e s. I empo a ily immobilizes ish o s udy
bu mus be ca e ully execu ed o minimize s ess and accoun o species-speci ic
a iabili y in e ec i eness. Va ious apping echniques (like yke ne s, minnow aps, o
c ab po s) and line ishing ( od and eel su eys) a e also adi ional ways o sample ish.
Al hough no a su ey me hod pe se o communi y assessmen , ma k- ecap u e
echniques a e a adi ional app oach o es ima e popula ion size and ack ish
mo emen s (Tho s einsson, 2002).
Figu e 2. T adi ional ish moni o ing echniques ac oss aqua ic en i onmen s. The illus a ion depic s
a ious con en ional sampling me hods: elec o ishing and cas ne ing in eshwa e ecosys ems, and
bo om awling, pu se seining, and di e -based obse a ions in ma ine en i onmen s.
GENERAL INTRODUCTION
11
These con en ional me hods ha e collec i ely buil he ounda ion o ishe ies
science and aqua ic ecology. They ha e allowed scien is s o ca alog species, moni o
ends, and manage ishe ies o decades. Fo example, conduc ing ex ensi e ne ing
su eys ac oss many si es equi es signi ican manpowe and can only co e limi ed
spa ial a eas a a ime (Sch amm J e al., 2002). Many me hods also demand axonomic
expe ise o iden i y species mo phologically, which can be di icul o la al o c yp ic
species. Some habi a s (deep wa e s, la ge i e s a lood s age, pola seas unde ice) a e
logis ically ha d o dange ous o sample wi h adi ional means, lea ing gaps in
moni o ing co e age. Addi ionally, as no ed, me hods like awling o elec o ishing can
dis u b habi a s and s ess non- a ge ish g oup (Fiona, 2014; Mun adas e al., 2014).
While con en ional moni o ing emains essen ial and i eplaceable in many con ex s (and
p o ides he baseline o which new me hods a e compa ed), in eg a ing mo e e icien
and less in usi e echniques can imp o e ou abili y o moni o ish biodi e si y on la ge
scales and wi h lowe impac . One o he mos g oundb eaking inno a ions in his ield is
he use o en i onmen al DNA (eDNA), which has opened new on ie s o aqua ic
moni o ing by de ec ing species h ough gene ic aces in he en i onmen a he han
di ec obse a ion o cap u e (Díaz-Fe guson & Moye , 2014).
2.2 En i onmen al DNA (eDNA) analysis: a e olu iona y
app oach o ish moni o ing and ecological assessmen
eDNA analysis has apidly eme ged as a ans o ma i e app oach o moni o ing
ish and o he aqua ic o ganisms (Rod íguez-Ezpele a e al., 2021). En i onmen al DNA
e e s o gene ic ma e ial ha o ganisms shed in o hei su oundings o ins ance, in
he o m o skin cells, scales, mucus, eces, u ine, eggs/spe m, o decaying issue. In an
aqua ic con ex , his DNA is suspended in wa e (o bound o sedimen s) and can pe sis
o days o weeks be o e deg ading. By collec ing en i onmen al samples (wa e ,
sedimen s, ai ) and ex ac ing DNA, we can de ec species by iden i ying hei unique
gene ic ma ke s, all wi hou needing o cap u e o e en see he o ganisms (Deine e al.,
2021). This app oach p o ides a non-in asi e, highly sensi i e, and cos -e ec i e
al e na i e o adi ional ish moni o ing echniques. eDNA me hodologies gene ally all
in o wo b oad ca ego ies depending on he moni o ing goals: a ge ed de ec ion and
communi y-wide me aba coding (Figu e 3).
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
12
Figu e 1. Schema ic o e iew o eDNA analysis o moni o ing aqua ic biodi e si y: This igu e illus a es
how a single d op o wa e con aining DNA om biological ma e ials (e.g., skin, scales, issue, mic obial
cells, and me abolic was e) is analyzed. The ex ac ed eDNA is p ocessed using qPCR o me aba coding
o iden i y species h ough gene ic ma ke s: 12S DNA (MiFish) o e eb a es, COI (Le ay/Folme ) o
in e eb a es, and 18S and 16S DNA o mic obial communi ies. Adap ed om Cha ez e al. (2021).
Ta ge ed eDNA de ec ion uses quan i a i e PCR (qPCR) o digi al PCR (dPCR)
o es o a speci ic DNA sequence unique o a axon o in e es . Whe eas eDNA
me aba coding allows o assess communi y composi ion h ough he simul aneous
ampli ica ion o DNA om mul iple species (Cha ez e al., 2021).
The ad an ages o eDNA sampling ex end beyond non-in asi eness; i s high
sensi i i y allows o he de ec ion o species a e y low popula ion densi ies, making i
pa icula ly use ul o iden i ying elusi e, mig a o y, o c yp ic species ha migh no be
cap u ed by adi ional me hods (Fu lan e al., 2019; Hinlo e al., 2017). Addi ionally,
eDNA-based moni o ing is highly scalable and e icien , equi ing signi ican ly less ield
e o and cos compa ed o adi ional su ey me hods while enabling apid biodi e si y
assessmen s ac oss la ge spa ial and empo al scales (Bálin e al., 2018). I also acili a es
ea ly de ec ion o in asi e species, allowing o p oac i e managemen be o e hese
species become es ablished and cause ecological o economic damage and long- e m
acking, in o ming conse a ion policies and ecosys em managemen (Deine e al.,
2017; Tsuji e al., 2024). As sequencing echnologies ad ance, eDNA-based app oaches
a e inc easingly being in eg a ed in o global biodi e si y moni o ing p og ams,
complemen ing and, in some cases, eplacing adi ional ish moni o ing me hods
(Suominen e al., 2024). I s abili y o p o ide p ecise, apid, and cos -e ec i e ecological
insigh s makes eDNA an indispensable app oach o ishe ies managemen , conse a ion,
and ecosys em sus ainabili y.
GENERAL INTRODUCTION
13
3. Ra ionale o he s udy
E ec i e biodi e si y moni o ing is ounda ional o ishe ies managemen and
conse a ion planning. Howe e , adi ional ish su ey me hods while aluable a e
o en limi ed by logis ical cons ain s, species-speci ic biases, and low sensi i i y,
pa icula ly o a e o c yp ic axa. En i onmen al DNA (eDNA) analysis has eme ged
as a ans o ma i e app oach ha can o e come many o hese challenges by de ec ing
species om gene ic ma e ial in wa e samples. Ye , despi e i s p omise, eDNA emains
unde u ilized and une enly alida ed ac oss ecological con ex s and geog aphical
egions.
This hesis add esses c i ical ques ions abou he easibili y, eliabili y, and
b oade applicabili y o eDNA-based moni o ing. Th ough global syn hesis and a ge ed
empi ical s udies, i explo es how eDNA pe o ms unde eal-wo ld condi ions, how i
compa es o con en ional me hods, and how i can be in eg a ed in o ecosys em
assessmen s and ishe ies amewo ks. The wo k spans species-speci ic de ec ion,
communi y-le el analysis, and ecological s a us e alua ion p o iding a mul i-
dimensional pe spec i e
4. Hypo hesis, aim and objec i e
4.1 Wo king hypo hesis
eDNA analysis is a sensi i e, non-in asi e app oach ha , when me hodologically
op imized, assess ish biodi e si y ac oss i e ine and es ua ine sys ems, cap u ing bo h
species-speci ic signals and communi y-le el a ia ion beyond he each o con en ional
su eys.
4.2 O e a ching aim and objec i es
To e alua e and ad ance he applica ion o eDNA analysis as a p ac ical and
scien i ically igo ous app oach o moni o ing ish biodi e si y and assessing ecological
condi ion, wi h a ocus on me hodological pe o mance, ecosys em-le el insigh s, and
egional applicabili y.
To achie e he o e all aim, he s udy de ines he ollowing speci ic objec i es:
Syn hesize he cu en s a e and ad ancemen s in eDNA applica ions o biodi e si y
moni o ing, wi h a ocus on me hodological de elopmen s in empe a e ecosys ems
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
14
and hei implica ions o applica ion in opical ishe ies, (Objec i e 1), which is
add essed in chap e 1.
E alua e he e icacy, scalabili y, and p ac ical applica ions o eDNA based
moni o ing wi h di e en con ex , iden i ying me hodological s eng hs, limi a ions,
and i s applica ion (Objec i e 2), which is add essed h oughou chap e s 2 and 3.
To assess de ec ion eliabili y and po en ial me hodological biases in eDNA-based
moni o ing by compa ing molecula da a wi h con en ional su ey echniques
(Objec i e 3), which is add essed h oughou chap e s 2 and 3.
To explo e he in eg a ion o eDNA-de i ed communi y da a in o ecological
assessmen amewo ks and ishe ies managemen s a egies, demons a ing i s
applica ion in ecological indices (Objec i e 4), which is add essed in chap e 3.
Toge he , hese objec i es p o ide mul i-le el in es iga ion om global con ex
o local applica ion o how eDNA can be s a egically employed o imp o e he
moni o ing and managemen o ish biodi e si y in bo h da a- ich and da a-de icien
en i onmen s.
5. S uc u e o he Thesis
This disse a ion is s uc u ed in o h ee main chap e s, wi h each chap e
add essing aspec s o mul iple esea ch objec i es ou lined abo e. Each chap e is w i en
in he o ma o an independen scien i ic s udy (wi h i s own in oduc ion, me hods,
esul s, and discussion) o allow in-dep h ocus on he speci ic esea ch ques ion, hough
some me hodological de ails may o e lap be ween chap e s. Following he h ee co e
chap e s, a gene al discussion will syn hesize he indings in he con ex o he
o e a ching hemes o he hesis.
The hesis is s uc u ed as ollows:
Chap e 1: Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o
opical ishe ies managemen
Chap e 2: Lessons lea ned om applying eDNA su eying o diad omous ish
de ec ion ac oss he no h-eas A lan ic egion
Chap e 3: Ad ancing ecological assessmen : The in eg a ion o eDNA
me aba coding in o an es ua ine ish index
GENERAL INTRODUCTION
15
CHAPTER 1
16
This manusc ip was published as:
Bhenda ka , M., Rod iguez-Ezpele a, N. Explo ing uncha ed e i o y: new on ie s
in en i onmen al DNA o opical ishe ies managemen . En i on Moni Assess 196,
617 (2024). h ps://doi.o g/10.1007/s10661-024-12788-8
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
17
Abs ac
T opical ecosys ems hos a signi ican sha e o global ish di e si y con ibu ing
subs an ially o he global ishe ies sec o . Ye hei sus ainable managemen is
challenging due o hei complexi y, di e se li e his o y ai s o opical ishes, and a ied
ishing echniques in ol ed. T adi ional moni o ing echniques a e o en cos ly, labou -
in ensi e, and/o di icul o apply in inaccessible si es. These limi a ions call o he
adop ion o inno a i e, sensi i e, and cos -e ec i e moni o ing solu ions, especially in a
scena io o clima e change. En i onmen al DNA (eDNA) eme ges as a po en ial game
change o biodi e si y moni o ing and conse a ion, especially in aqua ic ecosys ems.
Howe e , i s u ili y in opical se ings emains unde explo ed, p ima ily due o a se ies
o challenges, including he need o a comp ehensi e ba code e e ence lib a y, an
unde s anding o eDNA beha iou in opical aqua ic en i onmen s, s anda dized
p ocedu es, and suppo i e biomoni o ing policies. Despi e hese challenges, he po en ial
o eDNA o sensi i e species de ec ion ac oss a ied habi a s is e iden , and i s global
use is accele a ing in biodi e si y conse a ion e o s. This e iew akes an in-dep h look
a he cu en s a e and p ospec s o eDNA-based moni o ing in opical ishe ies
managemen esea ch. Addi ionally, a SWOT analysis is used o unde sco e he
oppo uni ies and h ea s, wi h he aim o b idging he knowledge gaps and guiding he
mo e ex ensi e and e ec i e use o eDNA-based moni o ing in opical ishe ies
managemen . Al hough he discussion applies wo ldwide, some speci ic expe iences and
insigh s om Indian opical ishe ies a e sha ed o illus a e he p ac ical applica ion and
challenges o employing eDNA in a opical con ex .
CHAPTER 1
24
(ICAR-NBFGR, 2016), and his numbe is con inuously bols e ed by epo s o new
o biodi e si y (Chand a e al
beyond in ish, encompassing a wide a ay o 2934 c us aceans, 5070 molluscs, 765
echinode ms, 486 sponges, and 844 seaweeds (Jena & Gopalak ishnan, 2012).
Despi e his ich aqua ic biodi e si y, India is g appling wi h se e e h ea s o
biodi e si y loss. These h ea s ange om habi a des uc ion, in asi e alien species,
o e exploi a ion, clima e change, and pollu ion, all o which a e in e connec ed and
caused di ec ly o indi ec ly by human ac ions (UNEP, 2008). So a , 120 eshwa e ish
species (Lak a e al., 2010) and 36 ma ine ish species (IUCN, 2021) om Indian wa e s
ha e been lis ed as h ea ened. Recen s udies (Raj e al., 2021; Ve ma & T i edi, 2016)
habi a s. This highligh s he u gen need o ind al e na i e app oaches o boos ish
biodi e si y conse a ion and managemen .
The applica ion o ish eDNA analysis has been demons a ed as an e ec i e
app oach o aqua ic biodi e si y moni o ing and su eillance a ound he wo ld,
pa icula ly in he ace o changing en i onmen s (Biggs e al., 2015; Deine e al., 2015;
e al., 2020; Minamo o e al., 2012; Sigsgaa d e al., 2015; Thomsen e
al., 2012a, 2012b; T éguie e al., 2014). S udies ha e used eDNA o de ec speci ic
species o ish (A du a, 2019; B ys e al., 2021) and c us aceans (King e al., 2022) o
de ec whole communi ies (Bessey e al., 2020; Li e al., 2022; Zainal Abidin e al., 2022),
wi h di e en habi a such as i e s (Can e a e al., 2019; Gou e e al., 2020), ese oi s
(Li e al., 2022), lakes (Fujii e al., 2019), es ua ies (Ruan e al., 2022; Zou e al., 2020),
deep sea (Kawa o e al., 2021), ma ine p o ec ed a eas (Gold e al., 2021; Ma wayana e
al., 2022; Pasche e al., 2022), and co al ee (Wes e al., 2020). Mos o hese s udies
concluded ha eDNA app oaches ou pe o med s anda d cap u e-based biomoni o ing
ish su eys. Fu he mo e, ce ain ish species we e no obse ed using he ish cap u e
app oach, al hough eDNA-based app oaches de ec ed hem (Aglie i e al., 2021; Yao e
al., 2022). The inc eased species de ec ion sensi i i y o eDNA compa ed o adi ional
me hods esul s in a ia ions in species abundance o dis ibu ion, pa icula ly conce ning
a e species, which a e o en o conce n o being endange ed o non-na i e po en ially
leading o unce ain ies in conse a ion and esou ce managemen decisions (Je de e al.,
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
25
2011). The absence o speci ic ish species in moni o ing e o s can lead o misguided
managemen decisions based on inadequa e da a, which can nega i ely impac he
conse a ion o hose species and he ecosys ems hey inhabi (De Sil a & Medellín,
2001; Mo a e al., 2009). The de ec ion o species h ough eDNA analysis, no cap u ed
by adi ional me hods, may indica e hidden biodi e si y, highligh ing he impo ance o
in eg a ing complemen a y echniques o holis ic moni o ing and u u e managemen
s a egies.
3.2 Fish mig a ion pa e ns
Fish mig a ion is commonly obse ed in many species, whe e ish mig a e om
one place o wa e body o ano he . This mo emen can occu daily o an annual basis, o
e en once in a li e ime, and ans e se dis ances ange om a ew me e s o housands o
kilome es, om ho izon al o e ical (Dingle & D ake, 2007; Mye s, 1949). The cause
o mo emen is mainly ela ed o eeding o ep oducing; in ce ain ci cums ances, he
eason o mig a ion emains unknown (B önma k e al., 2014; O deix & Casals, 2024).
The e o e, gaining insigh in o he mig a o y ecology o ish species and unde s anding
how, when, and why hey mig a e a e c ucial (Lennox e al., 2019). In India, a signi ican
po ion o indigenous ish species, especially smalle ones, mo e locally egula ly o mee
hei undamen al biological needs. Apa om a ew excep ions, he majo i y o Indian
mig a o y ishes a e po amod omous (Bhenda ka e al., 2020; Das & Hassan, 2008).
F om he e iew o exis ing li e a u e, we ound ha he e is a dea h o in o ma ion
accessible on mig a ion beha iou pa e ns o Indian ishes, wi h he excep ion o a ew
obse a ions on he spawning mig a ions o he Indian shad Tenualosa ilisha (Bhaumik,
2015; Sa ka e al., 2021) and Indian mo led eel Anguilla bengalensis (Abdul Kadi e
al., 2017; A ai & Abdul Kadi , 2017). Reg e ably, diad omous ishes wo ldwide a e
unde h ea due o human ac i i ies such as habi a des uc ion, o e ishing, and clima e
change (Tama io e al., 2019). As such, i is c i ical o moni o hei spawning mig a ions
non-in asi ely o unde s and hei beha iou and assess popula ion heal h.
In empe a e egions, esea che s add ess his need by employing eDNA analysis
o in es iga e he mig a ion ba ie s o c i ically endange ed Eu opean eels (Hal o sen e
al., 2020), he ep oduc i e mig a ion o h ea ened endemic ish, and he spawning
mig a ions o Danube bleak and imba b eam (Ma uyama e al., 2018; Thalinge e al.,
2019; Ya suyanagi e al., 2020). Recen s udies ha e demons a ed he e icacy o eDNA
CHAPTER 1
26
in p obing and unde s anding he ecological habi a s o complex and ha d- o- each
ecosys ems, such as he mesopelagic and deep-sea en i onmen s (Allan e al., 2021;
Canals e al., 2021), whe e adi ional me hods such as deep-sea awle ha e limi s in
in o ma ion abou deep-sea ecology. D awing om he success ul applica ions o eDNA
analysis in empe a e egions, i s po en ial applica ion in opical a eas is e iden . In
opical egions, unde s anding he mig a o y pa e ns o indigenous ish species,
pa icula ly species like he Indian shad and Indian mo led eel wi hin la ge i e ine
ne wo ks, is pa amoun o e ec i e conse a ion e o s. Employing eDNA analysis
o e s a non-in asi e app oach o moni o ing spawning mig a ions and mo emen
pa e ns, e ec i ely illing he ecological in o ma ion gap highligh ed ea lie .
3.3 Rep oduc i e s a us
Comp ehensi e assessmen o ish s ocks usually equi es in o ma ion on
ep oduc i e pa ame e s, as unde s anding he ep oduc i e capabili y o indi idual ishes
wi hin he spawning popula ion impac s ec ui men (Bhenda ka e al., 2013; Wi hames
asce ain he spa ial and empo al dis ibu ion o spawning e en s (G an e al., 2009;
Ha ison e al., 1984; Rose, 1993) o de e mine popula ion es ablishmen o bo h
in asi e and ansloca ed na i e species and design and e alua e managemen ac ions
(Kea se e al., 2012; King e al
is c ucial o he conse a ion and managemen o species and/o popula ions (Bylemans
e al., 2017). Howe e , he e is a signi ican gap in unde s anding he in luence o ishing
on he ep oduc i e po en ial o comme cially impo an species in Indian wa e s
(Gopalak ishna Pillai & Sa heeshkuma , 2012; Sa hianandan e al., 2021). This
unde s anding is essen ial o making in o med managemen decisions and ensu ing
esou ce sus ainabili y.
The use o egula and apid moni o ing echniques is necessa y o a oid delays
in es ima ing hese pa ame e s and imp o e s ock managemen capabili ies (Hogga h,
2006). Howe e , ypical cap u e su eys a e labou -in ensi e, ime-consuming, and
ulne able o moni o ing biases such as obse e bias, geog aphical es ic ions, and alse
spawning miscoun s (Bylemans e al., 2017; Caswell e al., 2004; Diana e al., 2015; Ko
e al., 2013; Kos e e al., 2013; Mille e al., 2012). Addi ionally, hese p ocedu es can
inc ease mo ali y among he spawning s ock and eggs, pa icula ly o a e and
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
27
endange ed species, isking he su i al o popula ions (Engs ed e al., 2014; Tsukamo o,
2006; Wei e al., 2009). Consequen ly, non-in asi e moni o ing echniques like eDNA
sampling can p o ide c ucial in o ma ion wi hou dis up ing he spawning p ocess o
endange ing he su i al o species o popula ions. Se e al ecen s udies in empe a e
wa e s ha e demons a ed he u ili y o eDNA analysis in moni o ing spawning e en s
o a ious species, including endange ed Macqua ie pe ch (Bylemans e al., 2017),
Eu opean pe ch and whi e ish (Vau ie e al., 2022), sockeye salmon (Tillo son e al.,
2018), he iming o b eeding season o Chinese s u geon (Yu e al., 2021), and Danube
bleak and imba b eam (Thalinge e al., 2019). In opical egions, whe e ishes o en
exhibi di e se ep oduc i e s a egies and b eeding habi a s a e no well unde s ood
(Winemille e al., 2008), eDNA analysis could o e a aluable ool o moni o ing
spawning e en s. The obse ed inc eases in eDNA concen a ion-compa able o pa e ns
ound in empe a e s udies-a e o en in e p e ed as indica o s o ep oduc i e ac i i y,
including spawning agg ega ions, ac i e spawning, o he p esence o ich hyoplank on.
Howe e , he di e si y o ep oduc i e s a egies among opical ish can complica e
hese in e p e a ions. Addi ionally, en i onmen al ac o s such as empe a u e and wa e
low (Lema e al., 2024) add u he complexi y o eDNA anspo and a e, in oducing
po en ial biases and unce ain ies in i s de ec ion and quan i ica ion (Ba nes & Tu ne ,
2016; Ki ane e al., 2023).
3.4 Sys ema ic de ec ion o a - isk, a e, o c yp ic species
The cul u al and his o ical signi icance o biodi e si y conse a ion in India has
been emphasized o a long ime, wi h li e a u e, eligious w i ings, and Vedic sc ip u es
p omo ing na u e conse a ion (Dhee e al., 2019). Howe e , as ecen ly highligh ed a a
Dialogue Ea h o um, India is one o he coun ies mos h ea ened by biodi e si y loss
(Nikhil, 2020). Cu en adi ional moni o ing me hods elian on in asi e sampling ace
limi a ions due o he conse a ion s a us o hese species and challenge implemen a ion
ac oss all habi a s. In his con ex , he applica ion o eDNA no only o e comes he
limi a ions o p e ious app oaches bu also minimizes he isk o he species being
moni o ed. In ecen yea s, mul iple eDNA-based s udies in empe a e a eas ha e
success ully moni o ed endange ed ish (Akama su e al., 2020; Boye e al., 2013;
Sigsgaa d e al., 2015; Thomsen e al., 2012a, 2012b) and imp o ing he de ec ion and
quan i ica ion o a e ish species in emo e loca ions (Balasingham e al., 2018; Be gman
CHAPTER 1
28
e al., 2016; Cas añeda e al., 2020; Wilcox e al., 2013) using species-speci ic p ime s
and a p obe.
3.5 Ea ly-wa ning sys em o in asi e and alien species
The in oduc ion o non-na i e species in o eshwa e habi a s has had a
signi ican impac on he dis ibu ion and he exis ence o nume ous na i e ish species
(Gup a & E e a d, 2019; Knigh , 2010). These impac s can be seen a a ious le els
including gene ic, indi idual, popula ion, communi y, and ecological changes
(Cuche ousse & Olden, 2011; Ma e al., 2013; Sma e al., 2006). The issue o he
in asion o o eign species, ei he in en ionally o acciden ally, is subjec o in ense
deba e. Reasons o in oducing hese species ange om expanding species di e si y in
aquacul u e, s ocking in lakes and ese oi s, en iching o spo ishe y base, o
augmen a ion o he a ie y in he aqua ium indus y. Ne e heless, hese in oduc ions
pose se ious h ea s o he conse a ion o na i e Indian species (Dahanuka e al., 2011;
Raj e al., 2020, 2021), whe e mo e han 500 species (13.6%) o non-na i e species ha e
been iden i ied (Joshi e al., 2021). The ea ly de ec ion o hese species in eshwa e
habi a s is c i ical o p e en ing hei es ablishmen and mi iga ing hei de imen al
e ec s on indigenous species. Despi e he exis ence o guidelines o he impo o
in oduc ion o aqua ic o ganisms in India (Ponniah & Sood, 2002), moni o ing such
expansi e aqua ic esou ces emains challenging. Howe e , in asi e species a e usually
no de ec ed un il hey ha e al eady become widesp ead. Ne e heless, local ishe men
( om p ima y ishe ies coope a i e socie ies) play a c ucial ole in epo ing in asi e
species sigh ings in hei ne s.
In his con ex , he use o eDNA o moni o he p esence o non-na i e species
ac s as an ala ming sys em. In empe a e wa e s, Thomas e al. (2020) used a po able
eDNA de ice o de ec in asi e species in a ew hou s, e en in habi a s whe e adi ional
app oaches o de ec ion a e di icul and labou -in ensi e. Fo ins ance, eDNA
iden i ica ion has been used o de ec alien c ay ish and hei ac i i y pa e ns in la ge-
scale sc eening o lo ic sys ems (Chucholl e al., 2021). Ea ly de ec ion o in asi e
species is essen ial o p e en hei es ablishmen and mi iga e hei nega i e impac . The
eDNA app oach plays a signi ican ole in his p ocess by allowing o e icien
moni o ing o he dis ibu ion and popula ion dynamics o in asi e species, which can
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
29
in o m decision-making o p o ec na i e species and ecosys ems (Ambe g, 2019; A du a,
2019; Na di e al., 2019; T ebi z e al., 2017; Xia e al., 2018).
3.6 In e play o die s and opic in e ac ion
Ecosys em unc ioning signi ican ly elies on ophic webs, which e eal he
bio ic ela ionships be ween he li ing c ea u es in he en i onmen . T adi ional me hods
o ophic web analyses ely on ood and eeding s udies based on s omach analyses, s ill
widely used oday (Bhenda ka e al., 2014). Howe e , his me hod can be ime-
consuming and challenging, especially o iden i ying diges ed ood i ems om a e,
small, o c yp ic o ganisms (Be y e al., 2017; Boye e al., 2013). Mo eo e , echniques
such as adioiso opes, s able iso ope analysis, di ec species obse a ions, and a y acid
analysis ha e also been used o a lesse ex en (Mondal & Bha , 2021; Neu eld e al.,
2007).
Mo e ecen ly, DNA ex ac ed om gu , s omach, o aecal con en s, known as
gu eDNA, has acili a ed i s widesp ead adop ion ac oss di e se ecosys ems (Huyghe e
al., 2023; Jo e al., 2016). I also aids in e ealing no el ophic in e ac ions and
enhancing axonomy. S udies ha e shown ha eDNA me aba coding o ood i ems o e s
aluable insigh in o he eeding beha iou o species like g een sea u les (Díaz-Abad
e al., 2022) and ca ishes (Guille aul e al., 2017). When compa ed wi h adi ional
me hods, i has been no ed ha eDNA can de ec a b oade ange o ood i ems, making
e al., 2017; Yoon e al., 2017).
3.7 Popula ion gene ics and eDNA
The applica ion o eDNA in popula ion gene ics is s ill in i s ea ly phases (Adams
e al., 2019; Wang e al., 2021). Howe e , his eme ging a ea o eDNA, on he o he hand,
has he po en ial o enhance ou comp ehension o pas dis ibu ions (Pawlowski e al.,
2021), p esen s a us (Dussex e al., 2016; Thomsen & Wille sle , 2015), and
beha iou al, ecological, and e olu iona y p ocesses (Adams e al., 2019) and in o m
conse a ion e o s. Popula ion gene ics s udies equi e he collec ion o issue samples
om s udy o ganisms, which can be logis ically di icul , esou ce-in ensi e, and
po en ially de imen al o bo h he o ganisms and hei en i onmen s. Recen s udies in
Indian popula ion gene ic esea ch ha e p edominan ly employed gene ic me hods o
s ock iden i ica ion, ocusing on comme cially impo an ish species along he Indian
CHAPTER 1
30
coas (S iHa i e al., 2022). These s udies ha e un eiled gene ic di e en ia ion be ween
en i onmen al ba ie s in luencing mig a ion pa e ns and la al dispe sal (CMFRI,
2023). In his con ex , eDNA analysis eme ges as a p omising op ion, ei he
complemen ing o in some cases eplacing i as a non-in asi e, cos -e ec i e al e na i e
o adi ional popula ion gene ics app oaches. Mo eo e , in biodi e se egions like India,
whe e biodi e si y loss is a p essing conce n, eDNA analysis can se e as a aluable ool
o moni o ing changes in popula ion size, assessing gene ic di e si y, and guiding
conse a ion s a egies. eDNA analysis p esen s an a ac i e al e na i e o he adi ional
app oach o popula ion gene ics esea ch, as i o e s a non-in asi e and cos -e ec i e
way o s udy gene ic a ia ion wi hin and be ween popula ions o di e en species. Fo
ins ance, Sigsgaa d e al. (2017) used eDNA ex ac ed om seawa e o es ima e he
popula ion size and haplo ype a ia ion o whale sha ks, while o he s udies ha e used
simila echniques o in es iga e a ious species in di e en egions and assign hem o
known haplo ypes (Be y e al., 2017; Pa sons e al., 2018). Some s udies ha e s a ed o
explo e he use o eDNA as a means o es ima ing popula ion size (Rou ke e al., 2022;
Spea e al., 2021). Howe e , a majo es ic ion o his app oach is he unce ain y o
how many indi iduals con ibu e o he de ec ed eDNA, making i di icul o con iden ly
compa e esul s wi h hose ob ained by geno yping known indi iduals. Fu he mo e,
while me aba coding has he po en ial o e eal ine-scale di e si y pa e ns, i s
e ec i eness is limi ed by he lack o comp ehensi e e e ence da abases o opical
species, a limi a ion highligh ed nex in he sec ion on ba code e e ence lib a ies.
3.8 Na u al sample s DNA (nsDNA)
In he con ex o en i onmen al DNA s udies, na u al sample s would be an
eme ging complemen a y app oach o biodi e si y moni o ing and assessmen . These
na u al sample s could be o example sponges (Ma iani e al., 2019) o gu con en s o
in e eb a es (Cal ignac-Spence e al. 2013; Ca alho e al., 2022; Rod íguez-Cas o e
al., 2023), which ac as il e s e aining eDNA om he en i onmen , which can hen be
ex ac ed o communi y analyses. Recen s udies in he opics ha e explo ed he use o
na u al sample s eDNA; o example, Tu on e al. (2020) ex ac ed DNA om sponges
o assess he ma ine ish di e si y in Nha T ang Bay (Vie nam), whe eas Meekan e al.
(2017) conduc ed a s udy in Baa A oll, Maldi es, ocusing on he popula ion s uc u e o
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
31
whale sha ks by isola ing and sequencing whale sha k DNA om a copepod, Panda us
hincodonicus
and na u al sample s can enhance he unde s anding o ish popula ions and ecosys ems,
he eby p o iding aluable insigh s o biodi e si y moni o ing and conse a ion e o s.
3.9 Addi ional applica ions o eDNA in he ishe ies sec o
The adop ion o eDNA in aqua ic esea ch is apidly expanding. The eDNA
analysis app oach has shown po en ial in a ious sec o s, such as aquacul u e, disease
su eillance, sea ood indus ies, and he de ec ion o o ganic ca bon in he ocean.
Globally, diseases a e majo cons ain and pose signi ican challenges o he aquacul u e
sec o , including in India (Bagum e al., 2013; Boha a e al., 2024; Sahoo e al., 2013;
S en i o d e al., 2020). Fo ins ance, sh imp cul u e in India su e ed a s agge ing o al
loss wo h US$ 1.02 billion, wi h an annual loss o 0.21 M o sh imp a ibu ed o
diseases (Pa il e al., 2021). Nume ous s udies ha e showcased he po en ial o eDNA o
he iden i ica ion and quan i ica ion o po en ial pa hogens in aquacul u e si es, which is
c ucial o disease isk assessmen (Díaz-Fe guson & Moye , 2014; Dully e al., 2021;
Hu e e al., 2015; Pe e s e al., 2018; Schus e e al., 2023; Shea e al., 2020; Taengphu
e al., 2022; T ujillo-González e al., 2019). In 2022, he Wo ld O ganisa ion o Animal
ou lined i s bene i s and limi a ions (Boha a e al., 2024). The in eg a ion o eDNA
me hodologies o e s p omise o e olu ionizing disease su eillance and enhancing
animal heal h moni o ing sys ems in aquacul u e, especially in India whe e diseases pose
signi ican challenges. Howe e , u he esea ch and conside a ion o bo h bene i s and
limi a ions a e essen ial o ully ha ness he po en ial o eDNA in disease- ela ed
challenges. Fu he mo e, eDNA has been used o iden i y he sou ce o o ganic ca bon in
e al., 2021; Ge aldi e al., 2019;
Ree e al., 2017). All coas al we lands, including mang o es, ma shes, and seag ass, a e
conside ed blue ca bon ecosys ems (Adame e al., 2024). Among hese, opical coas al
we lands a e pa icula ly p oduc i e (Wood o e, 2019) and se e as po en ial sou ces o
blue ca bon (Adame e al., 2019, 2024). Howe e , iden i ying o ganic ma e sou ces in
hese ecosys ems is complex due o a iable iso opic alues among plan species, issues,
and mic ohabi a s (Blai & Alle , 2012; Ma chand e al., 2003). Dis inguishing
CHAPTER 1
32
(Sain ilan e al., 2013). Complemen a y me hods, like eDNA and compound-speci ic
iso opes, can educe unce ain y in iden i ying sou ces (Ree e al., 2017), enhancing ou
unde s anding o ca bon luxes in ma ine sys ems. In addi ion, eDNA analysis has been
used o es he easibili y o a wide ange o ish species di e si y in sea ood. By de ec ing
and iden i ying he DNA o ish species in sea ood p oduc s, eDNA analysis can help
imp o e ood sa e y and aceabili y, p e en aud, and p o ide in o ma ion on he
sus ainabili y o ishe ies (Lee e al., 2021; Richa ds e al., 2022). By in eg a ing
complemen a y me hods and ad ancing scien i ic unde s anding, eDNA analysis can
con ibu e signi ican ly o enhancing he sus ainabili y and esilience o he ishe ies
sec o in opical egions.
4. Challenges and limi a ions o eDNA
While eDNA analysis holds p omising p ospec s o ad ancing he unde s anding
o aqua ic ecosys ems, i is impo an o no e i s associa ed challenges. This is pa icula ly
e iden in he con ex o India, whe e ce ain speci ic hu dles mus be o e come o
e ec i e implemen a ion. In he con ex o his e iew, we b ing in o ocus he p incipal
issues and majo challenges ha a ise up igh away and cu en ly limi he u ili y o
eDNA in he Indian scena io. These challenges a e ou lined below.
4.1 Ba code e e ence lib a ies
One o he mos signi ican challenges in using eDNA analysis o aqua ic
biomoni o ing is he lack o comp ehensi e e e ence da abases o nume ous axa (Je de
e al., 2021; S oeckle e al., 2020; Thomsen & Sigsgaa d, 2019). This gap limi s he
accu a e iden i ica ion o species based on eDNA. Al hough he ICAR-Na ional Bu eau
o Fish Gene ic Resou ces (ICAR-NBFGR) has c ea ed a da abase on Indian ish species
(Jena & Gopalak ishnan, 2012), he e is s ill a need o comp ehensi e DNA ba code
e e ence lib a ies o Indian aqua ic auna o ully ha ness me aba coding o aqua ic
biomoni o ing.
A p esen , he cumula i e lis o ish species ound in Indian wa e s,
encompassing eshwa e , ma ine, and b ackish en i onmen s, is eco ded a 2617 species
(F oese & Pauly, 2023). The da a we ha e o he COI, 12S, 16S, and cy b gene eco ds
show 67,576; 11,823; 9745; and 33,772 sequences, espec i ely. While some genes like
COI ha e ela i ely high species co e age (73%), o he s like 16S, 12S, and cy b, wi h
Explo ing uncha ed e i o y: new on ie s in en i onmen al DNA o opical ishe ies managemen
33
co e age anging om 49 o 55%, demons a e subs an ial oom o imp o emen . This
une en dis ibu ion o gene eco ds may lead o biases in species de ec ion and
quan i ica ion, making a holis ic unde s anding o biodi e si y challenging (Figu e 3).
These indings unde sco e he p essing need o expand he e e ence sequence lib a y
wi h a balanced inclusion o all ou genes o a mo e nuanced and accu a e communi y
composi ion assessmen .
Figu e 3. Gap analysis o e e ence da abase o ish species ound in Indian wa e s ob ained as in Cla e e al. (2023).
Each ba indica es he pe cen age o species o which a leas one sequence o each gene sequence is a ailable, wi h
he o al numbe o species wi h a ailable sequences and he numbe o sequences shown abo e he ba in black o in
colou
Despi e ongoing e o s o expand he co e age o he e e ences da abase, mo e
igo ous e o s a e needed o exploi eDNA analysis as a uly e ec i e ool o he
assessmen o biodi e si y and he conse a ion o Indian wa e bodies. Se e al coun ies,
such as Aus ia (ABOL), Finland (FinBOL), No way (No BOL), Ge many (GBOL), and
Aus alia (NBDL-h ps:// esea ch.csi o.au/dnalib a y/), ha e es ablished hei own
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
40
41
This manusc ip was p ep in as:
Bhenda ka , M., Cla e , C., Mendibil, I., F aija-Fe nández, N., Nachón, D. J.,
A., A daiz, J., Diaz, E., Lambe , P., Lassalle, G., & Rod iguez-Ezpele a, N. (2025).
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss
he no h-eas A lan ic egion. bioRxi (Cold Sp ing Ha bo Labo a o y).
h ps://doi.o g/10.1101/2025.01.31.635873
CHAPTER 2
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
42
Abs ac
Regula moni o ing o diad omous ishes is c i ical o in o m hei managemen
and conse a ion. Ye , he in-si u da a collec ion hese species is challenging due o hei
complex li e cycle and low abundance. Focusing on he sea lamp ey (Pe omyzon
ma inus, Pe omyzon idae) and he Eu opean shads (Alosa alosa and A. allax,
Clupeidae), emblema ic diad omous ishes in he No heas A lan ic egion, his s udy
le e ages he use o wa e en i onmen al DNA (eDNA) samples o moni o hei
dis ibu ion ange. Fo ha aim, we de eloped quan i a i e PCR (qPCR) and digi al PCR
(dPCR) assays and applied hem o de ec sea lamp ey and Eu opean shad DNA in a
ne wo k o 44 i e basins ac oss Spain, F ance, I eland, and he UK. We ound ha qPCR
e icien ly de ec ed p esence/absence o shads, while he highe sensi i i y o dPCR was
essen ial o de ec ing he lowe abundan and pa ly sessile beha ing sea lamp ey in he
amoun o wa e collec ed. Mo eo e , sea lamp ey showed signi ican ly lowe eDNA
copies pe li e o wa e compa ed o shads, p obably due o hei la ae spending se e al
yea s bu owed wi hin so sedimen s, educing eDNA shedding in o he wa e column.
The in eg a ion o his o ical da ase s wi h his snapsho wide- anging s udy enhances ou
unde s anding o he dis ibu ion o sea lamp ey and Eu opean shad in A lan ic i e s.
Impo an ly, he lessons lea ned wi hin his in e na ional collabo a ion a e c i ical owa ds
a p e ailing amewo k o conse a ion o mig a o y ishes, highligh ing he need o
well-designed sampling s a egies coupled wi h species-speci ic assays applied o eDNA
samples o bus long- e m moni o ing e o s o diad omous species.
CHAPTER 2
43
1. In oduc ion
An h opogenic ac i i ies, oge he wi h clima e change, can signi ican ly modi y
na u al habi a s and ecosys ems (Chu e al., 2005; Dodds e al., 2013). This is pa icula ly
c i ical o diad omous species, whose complex li e cycles, in ol ing a a ie y o habi a s
be ween i e s and open ocean, make hem mo e ulne able o any al e a ions (Chapa o-
Ped aza & de Roos, 2019; Limbu g & Waldman, 2009; Tama io e al., 2019).
Diad omous ishes a e emblema ic species wi h c ucial ecological oles, p o iding
nume ous ecosys em se ices (Almeida e al., 2023; Ashley e al., 2023; Naiman e al.,
2002). Thay can ei he be ca ad omous (mig a ing o sea o spawn) o anad omous
(mig a ing o i e s o spawn). The sea lamp ey (Pe omyzon ma inus Linnaeus, 1758)
and Eu opean shads (Alosa alosa Linnaeus, 1758 and A. allax Lacépède, 1803) a e
ecologically, e olu iona ily, and economically impo an anad omous species, which a e
p esen along he eas e n A lan ic coas (Almeida P R & Rocha d, 2015; Wilson &
Vene an a, 2019). Thei dis ibu ions and abundances ha e dec eased o e ime due o
he syne gis ic e ec o an h opogenic impac s, including clima e change, so ha hei
co e dis ibu ions a e now es ic ed o sou hwes e n Eu ope mos ly (Almeida e al., 2021;
Lassalle e al., 2008; Nachón e al., 2020). Despi e being ca ego ized by he In e na ional
Eu opean le el (F eyho , 2010a; F eyho , 2010b; F eyho & Ko ela , 2008a, 2008b;
Na u eSe e, 2013), hese species
Eu opean coun ies (Almeida P R & Rocha d, 2015; Limbu g & Waldman, 2009; OSPAR
Commission, 2009a, 2009b). Fo ins ance, in F ance and G ea B i ain, A. alosa is lis ed
P. ma inus is
e al., 2011; Nunn e
al., 2023; UICN Comi é ançais, 2019). This high le el o conse a ion conce n a
na ional le els and ac oss bounda y dis ibu ion o he species calls o conce ed in e -
basin conse a ion and managemen e o s (Guo e al., 2016; ICES, 2003; K i ze e al.,
2022; Ouelle e al., 2022).
In his con ex o gene alized decline, ob aining accu a e in o ma ion abou
diad omous species occu ence is essen ial o iden i y key pe iods and habi a s when and
whe e eeding, b eeding and mig a ion occu . Con inual change, especially al e a ions in
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
44
species home i e anges due o a ious p essu es, emphasizes he impo ance o
unde s anding hei mo emen s and habi a s (Beaula on e al., 2008; ICES, 2003). Ye ,
cha ac e izing he dis ibu ion o ish spa ially and empo ally is a challenging ask,
especially when conside ing ac o s like he scale o dis ibu ion, he complex li e his o y
o diad omous species, and esou ce cons ain s (Ciannelli e al., 2008). Con en ional
me hods, such as ma k ecap u e and elec o ishing ha e been ou inely used, bu ha e
hei own challenges, including di icul ies in deploymen in all habi a s (Lapoin e e al.,
2006; Pon e al., 2021). Mo eo e , hese me hods a e no only in usi e bu can also be
cos ly and labou -in ense (Lapoin e e al., 2006; Pon e al., 2021), as well as ine icien
in de ec ing low abundan species (Can e a e al., 2019; Piggo e al., 2021). The e o e,
using a cos -e ec i e, scalable and non-in asi e sampling me hod ha inc eases he
p obabili y o de ec ion is key o moni o ing a e aqua ic species wi h such a empo ally
es ic ed while spa ially wide dis ibu ion as anad omous ishes (Wes ho e al., 2022).
The analysis o en i onmen al DNA (eDNA) is a p omising and apidly e ol ing
app oach o aqua ic species dis ibu ion moni o ing (Bhenda ka & Rod iguez-Ezpele a,
2024; Naga ajan e al., 2022; Pawlowski e al., 2021; Rod íguez-Ezpele a e al., 2021),
wi h po en ial adap abili y in a changing wo ld (Thomsen e al., 2024). T aces o
o ganisms in he o m o game es, aeces, skin cells, sali a, blood, and o he bodily
subs ances con ain eDNA (Bohmann e al., 2014) ha can be u ilized o de e mine he
p esence o a species wi hin a speci ic a ea (Abbo e al., 2021; Da ison e al., 2019).
This me hodology has been ins umen al in examining spa io- empo al pa e ns a ound
spawning habi a s in i e s o P. ma inus (B acken e al., 2019; Mose e al., 2021) and
Alosa spp. (An ognazza e al., 2021; An ognazza e al., 2019). Mo eo e , eDNA-based
moni o ing has made i possible o iden i y p ospec i e nu se y g ounds and dis ibu ion
o sea lamp ey la ae (Bal aza -Soa es e al., 2022). Con e sely, he eDNA-based
app oach is also used o assess su eillance and con ol measu es o in asi e popula ions
o sea lamp ey in o he pa s o he globe whe e he species is conside ed as a pes
(Ginge a e al., 2016; Schloesse , 2018; Tkachuk & Dunn, 2020).
In his s udy, we conduc ed a b oad-scale su ey using eDNA o moni o he
geog aphical dis ibu ion o sea lamp ey and Eu opean shads in hei known ange o he
No h-Eas A lan ic egion. By using eDNA-based su eys, he goal was o p o ide a non-
in asi e, e icien and scalable app oach o moni o hese species ac oss mul iple i e
CHAPTER 2
45
basins in Spain, F ance, I eland and he UK. We aimed o add ess ou objec i es: i) o
assess he egional dis ibu ion o sea lamp ey and Eu opean shads; ii) o e alua e he
e icacy o eDNA analysis as a biomoni o ing ool wi hin his con ex ; iii) o compa e he
a iabili y o eDNA de ec ions be ween quan i a i e PCR (qPCR) and digi al PCR
(dPCR) me hods; i ) o de e mine eshwa e mig a ion limi s o sea lamp ey and shads
wi hin i e -es ua y sys ems du ing hei ups eam mig a ion. The i s wo objec i es
we e achie ed by compa ing qPCR-based eDNA de ec ions wi h e idence-based
knowledge o species occu ence ac oss 44 i e basins in Spain, F ance, I eland and he
UK, while he hi d and ou h objec i es we e based on dPCR-based eDNA de ec ions
om i e es ua ies wi hin Spain. As me hodology con inues o e ol e, he in eg a ion o
eDNA-based moni o ing is likely o become inc easingly essen ial in he assessmen o
diad omous species. This wo k imp o es ou unde s anding o he p ac icali y and
e iciency o eDNA analysis a a i e basin scale, p o iding a obus amewo k o
u u e esea ch and highligh ing he impo ance o a mul i-app oach o eDNA analysis
in e p e a ion.
2. Ma e ial and Me hods
2.1 Sampling loca ion and e e ence da a se
Wa e samples we e collec ed om a ne wo k o 44 i e basins ac oss Spain (20
i e s; 168 samples), F ance (2 i e s; 9 samples), he UK (15 i e s; 53 samples), and
I eland (7 i e s; 68 samples including 3 a sea close o he i e mou h). In he Basque
egion (Spain), addi ional wa e samples we e aken om ou es ua ies: Bidasoa,
Oia zun, U ola and Deba (15 samples) o in es iga e he abundance and dis ibu ion o
eDNA along he s e ch o i e leading o he ups eam si es h ough digi al PCR. The
sampling occu ed o e di e en yea s (2019 o 2021) in di e en egions, esul ing in a
o al o 313 samples (Figu e 1; Table S1). The selec ion o sampling si es was based on
he known his o ic dis ibu ion o sea lamp ey and shads in hei na i e ange wi hin hese
basins coupled wi h oppo unis ic sampling (Table S1). Fu he de ails on ansbounda y
eDNA sampling and analy ical me hods can be ound in he DIADES P ojec manual
(h ps://diades.eu/wp-con en /uploads/2020/04/WP6_1_Manual_Final_Ve sion-
comp ess%C3%A9.pd ).
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
46
Figu e 1. Geog aphical loca ion o i e basins sampled o in his s udy; main s ems a e ep esen ed wi h
a blue line. Each sec ion o he ba cha s indica es a sampling poin analysed h ough qPCR. Da ke
sec ions indica e sea samples aken nea he i e mou h (Slaney and Sui i e s) and ligh e sec ions
indica e sampling poin s loca ed in a luen s o he main i e basin (O ia i e ). See Table S1 o addi ional
de ails.
CHAPTER 2
47
To place eDNA-based indings in he con ex o expec ed p esence o absence, a
his o ical e idence e e ence da abase o he sea lamp ey and shads o each eDNA
sampling si e was c ea ed by combining p esence/absence da a om elec o ishing, aps,
and ne ope a ions, as well as p esence o downs eam ba ie s; e idence has been sou ced
om he scien i ic li e a u e o om da abase eposi o ies (Table S1). Fo each species,
o
he p esence o absence o he species.
2.2 Wa e sample collec ion and DNA ex ac ion
The olume o wa e sample il e ed anged om 1 o 30 li es (Table S2). Spanish
VigiDNA® c oss low il a ion capsules, espec i ely. I ish samples il e ed h ough 1.50
il e s we e u ilized (Table S2). All il e s we e kep ozen un il u he p ocessing. Fo
DNA ex ac ion, he Qiagen QIAamp DNA ki was used o Spanish and I ish samples,
while he F ench samples we e p ocessed using an in-house p ocedu e (Pon e al., 2018),
and UK samples we e ex ac ed using he DNeasy Powe Wa e S e i ex ki (Qiagen)
me iculously pe o med wi hin a specialized hood o p e en con amina ion. Each il e
was ex ac ed and analyzed indi idually, ensu ing he in eg i y o he DNA ex ac s om
each sepa a e wa e samples. The ex ac ed DNA was hen anspo ed o AZTI in Spain
o u he analysis. The concen a ion o he ex ac ed DNA was quan i ied using UV
spec ome y (The mo Scien i ic NanoD op ND-1000) and Qubi TM luo ome e (Li e
Technologies), and i s quali y was assessed h ough aga ose gel elec opho esis.
2.3 Species-speci ic de ec ion assay de elopmen
To de ec bo h species o Eu opean shads inhabi ing Eu opean wa e s (A. alosa
and A. allax), we designed genus-speci ic p ime s and a p obe o Alosa spp. a ge ing a
94bp agmen o he mi ochond ial cy och ome b (cy b) gene. To do so, all Alosa cy b
a ailable sequences we e e ie ed om GenBank (h ps://www.ncbi.nlm.nih.go ).
These sequences we e aligned and a sui able egion in which o de elop he speci ic assay
was iden i ied using he BioEdi so wa e (Ki mani, 2015). To ensu e he speci ici y o
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
48
he p ime and p obe se s, an in silico analysis was pe o med using BLAST (Al schul
SF, 1990), and no po en ial ampli ica ion o non- a ge DNA was de ec ed. Fo he
de ec ion o P. ma inus, we u ilized he assay de eloped by Mose e al. (2021). The
sequences o he p ime s and p obes used in his s udy a e de ailed in Table 1.
Table 1. P ime and p obe sequences used o speci ic ampli ica ion and de ec ion o Eu opean shads
Alosa spp. and sea lamp ey Pe omyzon ma inus
P ime Name Nucleoide sequence 5´ o 3´ Re e ence
Alosa_Fo ACATTTCAGTTTGATGAAACTTCGG
This s udy
(Alosa spp.)
Alosa_Re GAAGTGTAGTGTATAGCCAGGAA
Alosa_p obe AGGAATGTGTTTAGCGGCAC
Pma_Fo TTGGAGGCTTTGGCAACTG
(Gus a son e al., 2015)
(Pe omyzon ma inus)
Pma_Re TGTTTATACGAGGGAAGGCCATA
Pma_P obe CTAATACTTGGTGCTCCTG
2.4 Quan i a i e PCR (qPCR) analysis
Quan i a i e PCR analyses we e pe o med by combining he 5 µl o TaqMan
Fas Ad anced Mas e Mix (Applied Biosys ems), 0.2µl o each p ime ( o wa d and
e e se) and p obe (10 µM), 2 µl ex ac ed DNA (10 ng) and 2.4 µl Milli-Q wa e , o
adjus he o al eac ion olume o 10 µl. The p ocedu e was ca ied ou independen ly o
de ec he Alosa spp. and P. ma inus unde he ollowing condi ions: o Alosa spp., ini ial
50°C o 2 min and 95°C o 10 min, ollowed by 50 cycles al e na ing be ween 95°C o
3 s and 60°C o 20 s; and o P. ma inus, 50 cycles al e na ing be ween 95°C o 3 s and
55°C o 20 s. A o al o i e PCR eplica es we e analyzed o each sample, along wi h
posi i e and nega i e con ols. Genomic DNA (gDNA) ex ac ed om issue samples o
specimens collec ed in 2019 om he i e basins in he Basque Coun y by EKOLUR
En i onmen al Consul ing (Spain) was used as a posi i e con ol, wi h a 10- old s anda d
dilu ion se ies included on each qPCR pla e. A sample was conside ed posi i e o he
species i a leas one qPCR eplica e yielded a cycle h eshold (C - alue, indica ing he
numbe o cycles in qPCR needed o de ec he DNA signal) alue less han 40 (Takaha a
CHAPTER 2
49
e al., 2020; Wes ho e al., 2022). To alida e ha he PCR was no inhibi ed, an
addi ional analysis adding a known amoun o DNA (0.1 ng) o a a ge ed species
(In e nal Posi i e Con ol - IPC) o each sample was pe o med. The composi ion o he
PCR mix u e as well as he he mocycling condi ions we e he same as abo e, bu he
eac ion included 2 µl o IPC, wi h an adjus men o he olume o wa e . A sample was
iden i ied as inhibi ed i he C alue was delayed o ailed o ampli y in his PCR.
2.5 Digi al PCR (dPCR) analysis
Digi al PCR (dPCR), u ilizing he QIAcui y One, 5plex (Qiagen), was used o
alida e and compa e he de ec ion sensi i i ies be ween qPCR and dPCR on samples
collec ed om Spanish i e s. Addi ionally, we analyzed a new se o samples ha we e
collec ed along ansec s ex ending om he es ua ies o i e s Bidasoa, Oia zun, U ola
and Deba. The p ime and p obe se s u ilized in he dPCR assays we e consis en wi h
hose used in he qPCR analyses, wi h ROX-labelled p obes designa ed o Alosa
de ec ion and Cy5-labelled p obes o P. ma inus de ec ion. Each dPCR eac ion
con ained 10 µl o QIAcui y P obe PCR Ki , 3.2 µl o p obe mix, 2 µl o ex ac ed DNA,
and 24.8 µl o Milli-Q wa e , esul ing in a o al eac ion olume o 40 µl. This 40 µl
eac ion olume was hen ans e ed in o mic o luidic dPCR nanopla es (QIAcui y)
capable o accommoda ing 24 samples, wi h each well di ided in o up o 26,000
pa i ions. Each o hese pa i ions enables indi idual PCR eac ions o occu wi hin hem.
The nanopla e was hen loaded on o he digi al PCR ins umen (QIAcui y One, 5plex)
and subjec ed o an au oma ed wo k low a e quan i ying he cycling p o ocol. The
he mal cycle was execu ed unde he ollowing condi ions: an ini ial s ep a 95°C o 2
minu es, ollowed by 40 cycles al e na ing be ween 95°C o 15 seconds and 60°C o 60
seconds. Each pla e included posi i e con ols (s anda d dilu ion se ies wi h issue
samples) and nega i e con ols (no empla e con ols, NTC). Fo de ec ion, he ROX
luo escence channel was engaged o moni o Alosa spp. ampli ica ion, whe eas he Cy5
luo escence channel was used o P. ma inus ampli ica ion. Fluo escen images om all
PCR wells we e acqui ed and analyzed; pa i ions indica ing he p esence o he a ge
molecule we e disce ned by hei ele a ed luo escence in ensi y.
The common h eshold alue o luo escen in ensi y (RFU) was se manually, in
acco dance wi h Qiagen handbook ecommenda ions (Qiagen, 2022), wi h bo h nega i e
and posi i e con ols in each eac ion (Passe a e al., 2023). This choice allowed us o
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
56
Figu e 5. Spa ial abundance pa e ns o eDNA de ec ions using dPCR ac oss Spanish sampling si es, whe e
he do size ep esen s he eDNA concen a ion (copies/L) o a) lamp ey and b) shads in each sampling
poin and ed c osses indica e samples whe e no DNA was de ec ed (ND). Fo Bidasoa i e in 2020, he
do s ep esen he a e age concen a ion (mean) o he i e sampling da es wi hin he yea in which wa e
was collec ed. Acco dingly, he connec ed sca e plo s show a b eakdown o he esul s o he sampling
da es wi hin he yea . Only esul s o hose da es o which h ee sampling poin s we e sampled and had
a leas one o hem posi i e a e shown.
S a is ical analysis e ealed no signi ican di e ences be ween eplica es o
ei he P. ma inus (p- alue = 0.9428) o Alosa spp. (p- alue = 0.3887), con i ming he
consis ency o ou sampling me hodology. O e all, eDNA concen a ions o P. ma inus
we e signi ican ly lowe han hose o Alosa spp. (Figu e 5). In he Basque Coun y, P.
CHAPTER 2
57
ma inus eDNA was mainly de ec ed in he Bidasoa, Oia zun, U umea, O ia, Ba badun
and Kadagua i e s, whils in Galicia, posi i e de ec ions we e eco ded in he Eo,
Anllóns, Umia, Ulla and Tamb e i e s (Figu e 5a).
On he o he hand, Alosa spp. displayed a mo e es ic ed dis ibu ion, wi h de ec ions
con ined o he downs eam o he Bidasoa and Deba i e s in bo h yea s, while no
de ec ions we e eco ded in he es ua y o any o he basins in 2019 (Figu e 5b). A
consis en pa e n o eDNA de ec ion was obse ed, wi h highe concen a ions ound a
downs eam si es and p og essi ely lowe concen a ions ups eam, ega dless o he
sampling pe iod (Figu e 5).
4. Discussion
In his s udy, we buil on exis ing knowledge o P. ma inus and Alosa spp.
dis ibu ion h ough a esea ch ini ia i e spanning 44 i e sys ems ac oss Eu ope. This
e o was made possible h ough in e na ional collabo a ion among esea che s, enabling
a la ge-scale applica ion o he eDNA app oach o assess he dis ibu ion o wo
diad omous ishes, bo h o signi ican conse a ion conce n in he No heas A lan ic
egion. He e we sha e key p ac ical lessons om his ambi ious endea ou , wi h he goal
o guiding simila applica ions o eDNA o moni o ing diad omous ish in simila and
o he con ex s.
4.1 De ec ion disc epancies among species
He e, we concu en ly moni o ed he p esence o bo h P. ma inus and Alosa spp.
using he same eDNA sample. Bo h species a e anad omous and exhibi simila habi a
p e e ences du ing hei spawning mig a ions. Du ing sp ing, adul Alosa spp. and P.
ma inus mig a e o i e s o spawn, a e which mos die (Sil a e al., 2013). A e
ha ching, ju enile Alosa hen mig a e o he sea in la e summe and au umn (Ap ahamian
e al., 2003), while P. ma inus la ae (ammocoe es) emain bu ied in he i e bed o
yea s be o e becoming pa asi ic ju eniles (OSPAR Commission, 2009). This bu ied
la al s age (Almeida e al., 2023; Limbu g & Waldman, 2009), and he ac ha we
conduc ed su ace wa e eDNA sampling, migh esul in low eDNA de ec ion a es o
P. ma inus. Con e sely, Alosa spp., wi h a p ima ily pelagic habi a and high mobili y
du ing spawning, a e mo e likely o elease eDNA in o he wa e column du ing
mig a ions. Acco ding o hese p edic ions, in ou s udy, eDNA de ec ion a es be ween
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
58
he wo species di e ed: Alosa spp. was de ec ed in 40% o he si es whe e i was expec ed
whe eas P. ma inus was de ec ed in 29%. While o he alid a gumen s could be made,
hese esul s and ini ial in e p e a ions highligh he impo ance o inco po a ing species-
speci ic beha iou pa e ns and habi a p e e ences in o eDNA sampling design and esul
analysis (Bal aza -Soa es e al., 2022; Clemens e al., 2022).
4.2 When and how o sample
The oppo unis ic na u e o his in e na ional moni o ing su ey o diad omous
ish led o dis inc sampling app oaches by each ins i u ion, which may ha e in luenced
de ec ion a es. These a ia ions included sampling imes, loca ions, collec ed wa e
olumes, and il e po e sizes and ypes. E o s we e made o synch onize mos o he
eDNA sampling wi h he mig a ion pe iod o bo h species, assuming highe eDNA
shedding a es du ing his ime (Thalinge e al., 2019). Howe e , his synch oniza ion
was no ully achie ed o P. ma inus (Kelly & King, 2001; McIn y e e al., 2007; Sil a
e al., 2019; Sil a e al., 2013; Ta e ny & Elie, 2009). In he Basque Coun y only,
sampling was pe o med du ing ups eam and downs eam mig a ion, while all o he
egions we e sampled only du ing downs eam mig a ion.
Bo h Alosa spp. and P. ma inus eDNA we e de ec ed du ing ups eam mig a ion
a expec ed loca ions, bu sea lamp ey was la gely unde ec ed on downs eam mig a ion,
likely due o misma ches in iming wi h peak downs eam mig a ion and lowe eDNA
shedding a es in su ace wa e . In con as , he success ul de ec ion o sea lamp ey was
epo ed in Galicia as well as in he Tama and Dee i e s, likely due o he high
popula ion densi y in hese a eas, which inc eased he likelihood o eDNA p esence in
he wa e samples.
In e es ingly, he de ec ion a es did no appea o be signi ican ly in luenced by
While la ge po e sizes can acili a e he il a ion o g ea e wa e olumes, he eby
inc easing o al eDNA yield (Capo e al., 2020; Mächle e al., 2016), ou esul s sugges
ha single-species PCR de ec ion is mo e dependen on DNA concen a ion han on
il a ion pa ame e s (Eichmille e al., 2016). Despi e using same po e size (0.45 ),
F ench samples, which used 30L o wa e olume, esul ed in lowe eDNA de ec ion a es
a expec ed si es han Spanish samples, which used 1-2L o wa e olume. This
CHAPTER 2
59
obse a ion sugges s ha sampling la ge olumes o wa e does no necessa ily imp o e
de ec ion, and ha o he ac o s, such as popula ion densi y, iming, and eDNA
deg ada ion, may play mo e subs an ial oles.
Al hough we did no obse e a clea imp o emen in de ec ion wi h inc eased
wa e olume o po e size ac oss all cases, in con ex s whe e a ge species a e a low
abundance such as ou side he peak mig a ion pe iod o in es ua ine habi a s i may
s ill be bene icial o maximize il e ed wa e olume and conside la ge po e sizes o
inc ease he chances o eDNA cap u e. Howe e , his ecommenda ion should be aken
cau iously, as i is no ye suppo ed by consis en empi ical e idence ac oss sys ems, and
u he esea ch is needed o e alua e he impac o il a ion pa ame e s unde low-
concen a ion scena ios.
4.3 Me hodological di e ences
The compa ison be ween esul s o qPCR and dPCR e ealed in e -speci ic
di e ences. Fo Alosa spp., esul s o bo h app oaches a e simila wi h 96% o he
samples esul ing in conco dan esul s. In his case, only 6 ou o 158 samples exhibi ed
inconsis en esul s. The ou qPCR-posi i e bu dPCR-nega i e esul s may ep esen
alse posi i es, as hey we e cha ac e ized by only one o wo posi i e eplica es and high
cycle h eshold (C ) alues. Con e sely, he wo dPCR-posi i e esul s ha we e no
de ec ed by qPCR may be a ibu ed o low DNA quan i ies ha we e below he de ec ion
limi o qPCR. Fo P. ma inus, he conco dance a e d opped o 80%, wi h di e ing
esul s in 31 ou o 158 samples. In e es ingly, 8 samples we e posi i e by qPCR bu
nega i e by dPCR. O hese, six samples had only one o wo posi i e qPCR eplica es;
howe e , wo samples had h ee and ou posi i e eplica es wi h lowe C alues,
indica ing po en ial dPCR alse nega i es. dPCR u ilizes ex ensi e sample dilu ions
di ided in o housands o independen pa i ions assessed h ough Poisson s a is ics
(Qiagen, 2024). Signi ican dilu ion can p oduce pa i ions ha do no con ain he a ge
DNA, especially a low ini ial concen a ions (Whale e al., 2013), which migh explain
he obse ed alse nega i es. Addi ionally, 23 P. ma inus samples ha we e posi i e in
dPCR bu nega i e in qPCR highligh po en ial limi a ions in he sensi i i y o he qPCR
me hod o de ec ing low concen a ions o DNA. O e all, dPCR demons a es supe io
e icacy compa ed o qPCR o de ec ing species occu ing a low abundance. dPCR is
also ad an ageous as i p o ides p ecise quan i ica ion o numbe o eDNA copies, which
Lessons lea ned om applying eDNA su eying o diad omous ish de ec ion ac oss he no h-eas A lan ic egion
60
allows absolu e abundance compa isons be ween samples. Ye , o ensu e eliable dPCR
esul s, sample concen a ions mus be main ained wi hin he dynamic ange o educe
pa i ioning e o s, pa icula ly o samples o unknown concen a ion (Qiagen, 2024).
Sys ema ic op imisa ion o dilu ion ac o s imp o es he con idence o dPCR in
iden i ying low a ge DNA concen a ions, he eby educing alse nega i e a es. This
op imiza ion p ocess in ol es adjus ing he dilu ion le els o achie e he desi ed
sensi i i y and p ecision, which is pa icula ly impo an when dealing wi h low-
abundance a ge s (Jiang e al., 2022). While dPCR gene ally p o ides highe sensi i i y
and accu acy, qPCR may s ill be chosen in some con ex s due o i s lowe cos ,
pa icula ly in la ge-scale moni o ing scena ios whe e a o dabili y is a key conside a ion
(Zhang e al., 2024). This ade-o be ween cos and accu acy highligh s he impo ance
o selec ing he app op ia e me hod based on speci ic esea ch objec i es and a ailable
esou ces.
4.4 Can eDNA be used as eliable sou ces o p esence/absence
o diad omous ish?
The inding om his su ey e ealed inconsis encies be ween eDNA de ec ion
and expec ed occu ences o P. ma inus and Alosa spp. Focusing on si es whe e he
species we e expec ed, we iden i ied alse nega i es, which could be a ibu ed o low
abundance o he species, esul ing in low eDNA concen a ions in he dPCR o qPCR
assays. Because alse nega i es can mis ep esen species p esence and hinde
conse a ion e o s (Des oche s e al., 2010), i is impo an o educe hem by adap ing
sampling imes o coincide wi h peak mig a ion, especially du ing spawning pe iods,
il e ing la ge olumes o wa e , and applying mo e sensi i e me hods such as dPCR.
Focusing on he si es whe e he species was no p esen , only in he case o shad we
de ec ed h ee appa en alse posi i es; howe e , one o hem occu s only in he qPCR
esul s, only in one eplica e ield sample o wo, only in one ou o i e qPCR eplica es,
and wi h high C alues (39); he o he wo appa en alse posi i e loca ions (Inny and
Ilen i e s, I eland) did no ha e dPCR esul s a ailable, bu he qPCR posi i es we e
based on a single eplica e ou o i e and wi h high C alues (37 & 39). In iew o his,
all hese h ee appa en ly alse posi i es can be conside ed ue nega i es ins ead.
Focusing on he si es o which p esence o absence in he species was unknown, all cases
esul ed nega i e o P. ma inus. Howe e , o Alosa spp., we e ealed new si es whe e
CHAPTER 2
61
he species could be p esen . In e es ingly, in i e Deba (Spain), he ini ial assessmen o
Alosa
agency o e u n o he i e whe e hey ound Alosa spp. (Ekolu , pe sonal
communica ion). Fo his s udy, he a ailabili y o a comp ehensi e e e ence da abase
has enhanced ou unde s anding o he eDNA-based esul s, acili a ed in e p e a ion and
iden i ica ion o po en ial causes o alse nega i es and posi i es. The e o e, we p opose
eDNA as a complemen a y in o ma ion sou ce o diad omous species moni o ing, which
can be applied o inc ease ime and space co e age due o i s easy logis ic, non-
in asi eness and cos -e ec i eness.
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
62
CHAPTER 3
63
This manusc ip was p ep in as:
Bhenda ka , M., Canals, O., Ju ado, C., Mendibil, I., U ia e, A., Bo ja, A., &
Rod iguez-Ezpele a, N. (2025). Ad ancing ecological assessmen : The in eg a ion o
eDNA me aba coding in o an es ua ine ish index. bioRxi , 2025.2003.2031.645977.
h ps://doi.o g/10.1101/2025.03.31.645977.
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
64
Abs ac
In he ace o inc easing an h opogenic p essu es on es ua ine ecosys ems, he need o
e icien and eliable me hods o assess hei ecological s a us is essen ial. This s udy
dex (AFI)
o assess i s ecological s a us in es ua ine ecosys em o he Basque Coun y, Spain.
Su ace wa e eDNA sample and bo om awl su ey we e pe o med ac oss he mul iple
es ua ies, esul ing species da a we e used o calcula e AFI sco es unde di e en
scena ios. eDNA me aba coding consis en ly de ec ed highe ish species ichness han
awling, while bo om awling emained mo e e ec i e a cap u ing deme sal species.
Howe e , ecological classi ica ions om eDNA- and bo om awl de i ed da a displayed
low conco dance, la gely due o di e ing species assemblages and me ics con ibu ions.
These esul s emphasize he espec i e s eng hs and weaknesses o each me hodology
and he necessi y o me hod-speci ic calib a ion. Conside ing ha he AFI is calib a ed
using bo om awl da a, i s di ec applica ion o eDNA-de i ed species lis s may lead o
some inconsis encies. This s udy unde sco es he c i ical necessi y o es ablish eDNA-
speci ic e e ence condi ions and o ecalib a e index h esholds acco dingly. While
eDNA app oach may no en i ely eplace adi ional me hods, i s scalabili y, sensi i i y,
and minimal ecological dis u bances es ablish i as an essen ial complemen a y
applica ion wi hin moni o ing p og ams. This esea ch s ongly suppo s he u gen
ad ancemen o eDNA-based indices and he c i ical enhancemen o e e ence
condi ions o hei e ec i e inco po a ion in o ecological assessmen amewo ks unde
he Wa e F amewo k Di ec i e.
G aphical abs ac
CHAPTER 3
65
1. In oduc ion
Es ua ies, unc ioning as ansi ional zones be ween eshwa e and ma ine
en i onmen s, a e amongs he mos p oduc i e ecosys ems on Ea h, o e ing i al
ecosys em se ices o nea by communi ies (Adey, 2024; Ba bie e al., 2024). The
ecological impo ance o es ua ies lies no only in hei biodi e si y bu also in hei
abili y o egula e wa e quali y and p o ide habi a s o a ious species. Howe e ,
an h opogenic ac i i ies and en i onmen al s esso s inc easingly h ea en hese
ecosys ems, leading o signi ican educ ions in ecosys em se ices (Allen e al., 2023;
Ellio & Kennish, 2024; Jenne jahn & Mi chell, 2013). Addi ionally, clima e change
exace ba es hese h ea s, aising conce ns on he sus ainabili y o es ua ine supply o
se ices (Siemes e al., 2024).
In his con ex , assessing he ecological s a us o es ua ies is a p io i y, and a ious
assessmen me hods ha e been es ablished unde he Eu opean Wa e F amewo k
Di ec i e (WFD) o di e en biological elemen s (Bi k e al., 2012) such as
phy oplank on, ben hic lo a, ben hic in e eb a es and ish. Each o hese me hods a ies
be ween coun ies due o di e ences in he esponse o indica o species o ele an
s esso s, local species composi ion, sampling me hods and a ailable axonomic
esolu ion based on egional knowledge o lo a and auna (Bi k e al., 2012; Bo ja e al.,
2013).
which is speci ic o each aqua ic ecosys em, om which Ecological Quali y Ra io (EQR)
is de i ed by assessing he de ia ion o he calcula ed alue om his e e ence (Eu opean
Commission, 2000; Van De Bund & Solimini, 2007). Howe e , all o hem ha e been
ha monized h ough in e calib a ion among coun ies using hem (Eu opean
Commission, 2024).
Se e al ish-based indices ha e been p oposed in Eu ope (Pé ez-Domínguez e
al., 2012) and globally (Cab al e al., 2022)
de eloped p ima ily o e alua ing ecological quali y in he Basque Coun y es ua ies, in
Spain (Bo ja e al., 2004; U ia e & Bo ja, 2009). Nowadays, AFI is one o he mos
widely used indices o assessing he ecological quali y and bio ic in eg i y o ansi ional
wa e s (Souza & Vianna, 2020). I assesses EQR using composi ion and abundance da a
om bo om awl su eys. Howe e , sampling in es ua ine en i onmen s p esen s
signi ican logis ical and echnical challenges associa ed wi h physical cap u e o species
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
72
di e ences in AFI me ics ( ichness, pollu ion indica o s, la ish, omni o ous,
pisci o ous, and esiden species) be ween he eDNA-AFI and awl su ey. The Rela i e
Con ibu ion Ra io (RCR) was calcula ed o de e mine he p opo ional con ibu ion o
each ecological me ic o he AFI sco es (Luo e al., 2015). Fo each me hod, RCR was
compu ed as he pe cen age con ibu ion o a gi en me ic o he o al AFI sco e.
3. Resul s
3.1 Sampling e iciency o eDNA and bo om awling
All samples oge he , eDNA me aba coding yielded a o al o 16,496,674 eads
co esponding o 73 axa (60 axa axonomically assigned o he species le el and 13 a
he genus le el) om 30 o de s and 37 amilies (Table S7). Mulle s we e he dominan
g oup and accoun ed o app oxima ely 46% o he eads, wi h Chelon amada (35.1%)
and Chelon lab osus (7.7%) being he mos abundan . O he equen ly de ec ed species
wi h signi ican p opo ion o eads included Sa dina pilcha dus (8.8%), Dicen a chus
lab ax (6.8%), and Solea solea (6.7%). On he o he hand, he awling su ey cap u ed
310 indi idual ish classi ied in o 23 species o genus (1 specimen was iden i ied o
amily le el and wo specimens emained unclassi ied). Gobies we e he dominan g oup
in he ca ches, wi h Poma ochis us sp. and Gobius nige being he leading species,
ep esen ing 26% and 22% o o al ca ch, espec i ely. O he abundan cap u es we e he
la ish Solea solea (20%), and he seab eam Diplodus sa gus (14%).
As expec ed, eDNA me aba coding consis en ly de ec ed signi ican ly highe ish
species ichness compa ed o he adi ional awling app oach (p < 0.05) in all sampling
si es excep in h ee o hem: AME (Ba badun), AOKI (Oka) and OIAE (Oia zun)
(Figu e S1). A o al o 43 ish species iden i ied h ough he eDNA su ey a e lis ed in
he AFI da abase o which 24 we e no eco ded in he awl-based his o ical da abase
(Figu e 2).
CHAPTER 3
73
Figu e 2. Venn diag am showing he numbe o species ob ained in he eDNA me aba coding (o ange) and
bo om awling (g een) su eys, wi h each me hod suppo ed by a comp ehensi e e e ence da abase. The
e e ence includes his o ical awl ca ch da a om 2002-2019, while he eDNA su ey
u ilizes a local sequence da abase om he No heas A lan ic. I is impo an o no e ha he awling
e e ence da abase excludes species ha emain unclassi ied up o he genus and/o species le el.
Only se en species we e eco ded using bo h me hods, ye hey accoun ed o
87% o he awl caugh indi iduals and 24% o he eDNA sequence eads. The awling
su ey cap u ed 16 ish axa ha we e no de ec ed h ough eDNA me aba coding. O
hese, eigh axa we e absen in he e e ence da abase, while he emaining eigh , despi e
being in he e e ence da abase, we e no obse ed in he eDNA me aba coding.
Con e sely, eDNA me aba coding exclusi ely de ec ed 12 axa wi hin he his o ical
da abase and 30 addi ional axa no lis ed in he AFI da abase, many o which accoun ed
o less han 1% o o al eads (Figu e 2; Table S7).
3.2 Assessing awl and eDNA-based es ua ine ecological
s a us
AFI sco es we e calcula ed using bo h eDNA me aba coding- and bo om awl-
de i ed da a wi h and wi hou he inclusion o c us aceans. Fo eDNA me aba coding, he
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
74
analysis accoun ed o 35 di e en axa acco ding o he AFI lis and 17 di e en axa
based on he his o ical da abase (genus-based). The bo om awling based AFI
compu a ions included 25 ish axa, in addi ion o 13 c us acean species. Dispa i ies in
ecological s a us classi ica ions be ween hese me hodologies we e obse ed. Fo
ins ance, eDNA-
s a us, whe eas awl-
-
de i ed da a (Figu e 3).
No ably, when he AFI calcula ions we e es ic ed o ish ca ch da a, excluding
s a us, wi h he excep ion o sampling si e ANE, which indica ed a high s a us, and si es
ABM, OIAE, OIAI2, and UROM, which exhibi ed good s a us (Figu e 3b).
Figu e
3a). The wo eDNA-based AFI compu a ions exhibi ed nea -
0.90), e lec ing consis en esul s ac oss he wo da ase s. In con as , he wo awl-based
indica ing a iabili y in ecological s a us assessmen s when c us aceans we e conside ed.
C ucially, no ag eemen was obse ed be ween eDNA- and awl-de i ed AFI alues,
wi h kappa alues anging om -0.07 o -0.53 (Figu e 3b).
Addi ionally, signi ican di e ences we e obse ed in some ecological me ics
- es , p < 0.05, Figu e 4), namely species ichness, pollu ion
indica o species, p opo ions o la ish, pisci o ous species, and es ua ine esiden s. The
RCR analysis u he e ealed he in luence o indi idual me ics on AFI sco es.
CHAPTER 3
75
Figu e 3
AFI lis ed species), eDNA-B (conside ing his o ical da abase species), T awl wi h c us acean, and T awl
only ish (wi hou c us aceans). a) he le el o in e - a e conco dance be ween eDNA me aba coding and
bo om awl- n . b)
AFI sco es ac oss a ious sampling s a ions, wi h ba s ep esen ing di e en compu a ion app oaches.
Sco es ange om 0 ('Bad' s a us) o 1 ('High' s a us), wi h a colou g adien indica ing ecological s a us.
Some da a poin s o e lap due o iden ical AFI sco es a di e en si es. Ji e (wid h = 0.01, heigh = 0.01)
was applied o educe o e lap.
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
76
Figu e 4
Pollu ion Indica o Species (%), (C) In oduced Species (%), (D) Fla Fish Species (%), (E) Omni o ous
Species (%), (F) Pisci o ous Species (%), (G) Numbe o Residen Species, and (H) Residen Species The
sco es assigned indica e he o e all s a us (see Table 1), wi h blue ep esen ing a sco e o 5, yellow a sco e
o 3, and ed a sco e o 1.
Fo eDNA-based assessmen s, omni o ous species con ibu ed he mos ,
accoun ing o 52.8% o 56.7% o he AFI sco e. Pisci o ous species and esiden species
we e seconda y con ibu o s, wi h 17.9% o 16.5% and 12.2% o 13.5%, espec i ely. In
awl-based assessmen s, con ibu ions we e mo e e enly dis ibu ed. Residen species
had he highes impac (43.7% in ish-only analyses), ollowed by la ish (28 %) and
omni o ous species (17.6%).
4. Discussion
4.1 Me hodological con as s
This s udy demons a es he dis inc capabili ies o eDNA me aba coding and
bo om awling in cap u ing es ua ine ish assemblages, d i en by hei inhe en
me hodological di e ences. eDNA me aba coding de ec ed o e h ee imes mo e ish
species han bo om awling, emphasizing i s b oade axonomic each. These indings
align wi h p e ious s udies demons a ing ha eDNA consis en ly de ec s a highe
numbe o ish species compa ed o con en ional me hods in es ua ies (Gibson e al.,
CHAPTER 3
77
2024; Gibson e al., 2023; Saunde s e al., 2024; Zou e al., 2020). Howe e , his
di e ence should no be in e p e ed as an inhe en supe io i y o one me hod o e he
o he , bu a he as a e lec ion o hei undamen ally di e ences in sampling app oaches:
eDNA was collec ed om he su ace wa e du ing high ide and mainly de ec ed pelagic
and wa e -column-associa ed species, while bo om awling p ima ily cap u ed bo om-
dwelling ish. In addi ion, eDNA de ec s gene ic ma e ial p esen in he wa e column,
allowing o he iden i ica ion o species ha may no be physically p esen a he ime o
sampling (Je de, 2021); in con as o bo om awling, which is based on physical
cap u es.
Among he iden i ied species, only se en we e common o bo h me hods. These
se en axa, all deme sal, we e among he mos abundan ish in bo om awl ca ches
( ep esen ing 87% o he o al ca ch), ye hey accoun ed o only 24% o o al eDNA
eads. Since eDNA concen a ion in he wa e is gene ally assumed o co ela e wi h
biomass (Nakagawa e al., 2022), hei de ec ion h ough eDNA me aba coding sugges s
ha highly abundan deme sal species a e mo e amenable o be de ec ed in eDNA su ace
wa e samples han less abundan ones, which migh emain unde ec ed.
Despi e eDNA me aba coding cap u ing a highe numbe o species o e all, i s ill
ailed o de ec 16 axa cap u ed by awling, p edominan ly deme sal (including la ish)
species. Among hese, 8 species lacked e e ence sequences in publicly a ailable gene ic
da abases, p e en ing i s de ec ion, which ein o ces he dependence o eDNA
me aba coding on comp ehensi e and egionally ele an e e ence da abases o
accu a e species iden i ica ion (Bhenda ka & Rod iguez-Ezpele a, 2024; Cla e e al.,
2023; Ma ques e al., 2021). The emaining 8 species, despi e being p esen in he
e e ence da abase used o axonomic classi ica ion, we e no de ec ed in eDNA samples
likely due o hei low abundance (and he e o e expec ed low DNA concen a ion in he
wa e ) and/o limi ed e ical anspo o hei gene ic ma e ial o su ace wa e ,
sugges ing he need o inco po a ing bo om wa e laye s in eDNA sampling s a egy o
imp o e deme sal species de ec ion e iciency.
On he o he hand, eDNA me aba coding de ec ed 12 species no cap u ed by
bo om awling bu p e iously eco ded in he his o ical da abase, demons a ing i s
po en ial o de ec species ha may e ade physical cap u e due o hei beha iou , a i y,
o habi a p e e ence. These esul s align wi h p e ious s udies sugges ing ha bo om
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
78
awling, while e ec i e o deme sal species, may o e look species be e de ec ed
h ough eDNA (A zali e al., 2021; Ip e al., 2024; Zhou e al., 2022). An addi ional 24
axa p e iously un eco ded in he his o ical da abase we e also de ec ed h ough gene ic
. Fo
ins ance, he mos abundan species de ec ed ia eDNA me aba coding Chelon amada
and Sa dina pilcha dus we e no cap u ed by bo om awl and ha e no been p e iously
documen ed in he his o ical da abase. The absence o C. amada in bo om awl su eys
may be due o challenges associa ed wi h iden i ying mugilids h ough mo phological
ai s, as hey ha e his o ically been classi ied only o he amily le el in awl eco ds. In
con as , he absence o S. pilcha dus in bo om awl ca ches is likely a ibu able o i s
pelagic na u e and abili y o a oid bo om awling gea (Haugland & Misund, 2011).
While eDNA me aba coding imp o es biodi e si y de ec ion, i also in oduces
unce ain ies ega ding he o igins and ecological ele ance o de ec ed eDNA signals.
One o he p ima y challenges in in e p e ing eDNA-based de ec ions is he possible
in luence o eDNA anspo mechanisms, pa icula ly in es ua ine en i onmen s
cha ac e ized by complex hyd odynamics (McCa in e al., 2024). Thus, some species
de ec ions may esul om eDNA agmen s anspo ed om ups eam eshwa e
sou ces o in oduced h ough idal mo emen s om he ma ine en i onmen , a he han
indica ing ac ual species p esence a he sampling loca ion (Jeunen e al., 2019; Polanco
e al., 2021). Addi ionally, con amina ion om an h opogenic sou ces such as sewage
e luen s o ood was e could in oduce o eign DNA, po en ially in la ing species
ichness es ima es (Inoue e al., 2023). These ac o s highligh he need o e ined
analy ical app oaches o di e en ia e esiden species om ansien o ex e nal DNA
sou ces, pa icula ly in dynamic coas al ecosys ems whe e wa e mo emen can
signi ican ly impac de ec ion p obabili ies.
The obse ed di e ences in species composi ion be ween su ace wa e eDNA
sampling and bo om awling emphasize he impac o me hodological choices on
biodi e si y assessmen s (Aub y e al., 2024). I is a guable ha elying exclusi ely on
ei he me hod may unde - ep esen species di e si y, indica ing a complemen a y
pe spec i e. Su ace wa e sampling was chosen o i s ease and e iciency, making i a
non-in asi e, mo e cos -e ec i e and much less ime-demanding op ion compa ed o
bo om awling. Howe e , i s limi a ions in de ec ing ben hic species sugges ha
including eDNA samples om bo om wa e laye s could imp o e de ec ion o deme sal
CHAPTER 3
79
axa and help b idge some o he me hodological gaps obse ed. While his s udy did no
inco po a e bo om-laye eDNA sampling, he sugges ion o include i e lec s he b oade
aim o assembling a oolki ha cap u es a mo e comp ehensi e iew o es ua ine
biodi e si y. O e all, he signi ican di e ences in species composi ion be ween su ace
wa e eDNA me aba coding and bo om awling highligh he me hodological scope,
species de ec ion capabili ies, and inhe en biases o each app oach.
4.2 Beyond he ne : eDNA edge in es ua ine ecological
assessmen
The in eg a ion o eDNA me aba coding wi hin he AFI amewo k has e ealed
dis inc di e ences in ecological s a us compa ed o adi ional bo om awl-based
assessmen s. As p e iously discussed, hese di e ences a e p ima ily d i en by a ia ion
in species assemblages cap u ed by each me hod, which subsequen ly in luence he index
compu a ion. This in luence has con ibu ed o he lack o ag eemen be ween eDNA- and
awl-
wo me hods assess ecological s a us based on di e en species assemblages a he han
p o iding di ec ly compa able esul s.
The RCR analysis p o ides u he insigh in o how di e en species g oups
in luenced o e all AFI sco es ac oss he wo me hods. In bo om awl-de i ed AFI
assessmen s, esiden species (43.7%) had he s onges in luence, la gely d i en by
c us aceans. The ele ance o c us aceans in he bo om awl-based AFI was e iden ha
he e was poo ag eemen when bo om awl AFI calcula ions wi hou c us aceans,
unde sco ing hei c i ical ole, pa icula ly as key componen o he AFI o he
ecological assessmen o some Basque es ua y ypes (Bo ja e al., 2004). In con as ,
c us aceans we e no ep esen ed in ou eDNA esul s due o he use o ish-speci ic
p ime s ( eleo egion o he 12S gene; Valen ini e al., 2016), which we e selec ed o
a ge e eb a es. Ins ead, eDNA-de i ed AFI sco es we e p ima ily in luenced by
i s abili y o de ec species om mul iple ophic le els by cap u ing gene ic ma e ial
dispe sed in he wa e column. These indings unde sco e he necessi y o calib a ing
eDNA-based assessmen s o accoun o axonomic exclusions and di e ences in
communi y ep esen a ion.
Ad ancing ecological assessmen : The in eg a ion o eDNA me aba coding in o an es ua ine ish index
80
A majo challenge in in eg a ing eDNA-based ecological assessmen s is he lack
o speci ic e e ence condi ions. Since he AFI was o iginally de eloped using bo om
awl-de i ed da a, i s classi ica ion h esholds and ecological quali y class bounda ies
a e calib a ed o da ase s domina ed by deme sal and ben hic species. Howe e , eDNA
me aba coding de ec s species ha may no be well ep esen ed in bo om awl su eys.
Consequen ly, applying awl-de i ed e e ence condi ions o eDNA-based species lis s
may in oduce classi ica ion inconsis encies and di e ences in ecological assessmen s.
Es ablishing eDNA-speci ic e e ence condi ions is he e o e essen ial o ensu e ha
eDNA-based assessmen s p oduce ecologically meaning ul and compa able esul s. Once
speci ic eDNA-based e e ence condi ions a e implemen ed, g ea e con e gence
be ween eDNA- and bo om awl-de i ed ecological s a us is expec ed.
Beyond e e ence condi ions, he in eg a ion o eDNA in o AFI assessmen s also
equi es ca e ul in e calib a ion wi h adi ional me hods (Lepage e al., 2016). Since
awl-based AFI has al eady been calib a ed wi h o he mo phological ish sampling
echniques unde Eu opean egula o y amewo ks (Eu opean Commission, 2024),
ex ending his p ocess o eDNA me aba coding would help e ine indica o species
weigh ings, de ec ion h esholds, and index calcula ions. Such adjus men s a e essen ial
o ensu ing egula o y compa ibili y and me hodological consis ency ac oss moni o ing
p og ams. Despi e he challenges discussed in he p e ious sec ion, eDNA me aba coding
p esen s a compelling al e na i e in scena ios whe e con en ional cap u e echniques a e
imp ac ical o ecologically dis up i e. I s non-in asi e na u e minimizes habi a
dis u bance while o e ing a scalable and cos -e ec i e ool o es ua ine ecological
assessmen s.
5. Way o wa d
This s udy highligh s he ans o ma i e po en ial o eDNA me aba coding o es ua ine
ecological assessmen , bu s a egic ad ances a e needed o ensu e i s e ec i e in eg a ion
and long- e m applicabili y. Fi s , he de elopmen o eDNA-speci ic e e ence
condi ions is essen ial o ensu e ha ecological s a us classi ica ions a e compa able o
adi ional AFI assessmen s. This equi es he de elopmen o in e calib a ion p o ocols,
ecalib a ion o quali y class bounda ies and e inemen o de ec ion h esholds o
imp o e compa ibili y and consis ency o ecological assessmen s. Second, add essing
axonomic gaps in gene ic e e ence da abases emains a p io i y o minimize alse
CHAPTER 3
81
nega i es and misclassi ica ions. Addi ionally, op imizing sampling s a egies by
inco po a ing bo om wa e samples could imp o e he de ec ion o deme sal axa,
unde ep esen ed in eDNA samples collec ed om he wa e su ace. Mo ing o wa d,
we ecommend he de elopmen o no el eDNA-speci ic indices ailo ed o molecula
da a cha ac e is ics, which will enhance hei applica ion in es ua ine ecological
assessmen . Wi h hese ad ancemen s, eDNA me aba coding can e ol e in o a
s anda dized, non-in asi e ool o long- e m es ua ine moni o ing and assessmen .
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
88
p o ided wi h a baseline o e alua ing eDNA de ec ions aligned wi h known communi y
composi ion.
2.1 False posi i es: con ex is e e y hing
When eDNA de ec ed species no p e iously eco ded in a gi en si e, i aised
impo an ques ions: we e hese de ec ions e idence o p e iously undocumen ed
p esence, o we e hey a i ac s caused by con amina ion, DNA anspo , o
me hodological e o ? While con amina ion emains a conce n in PCR-based me hods,
we minimized his isk h ough s ic p o ocols including ield blanks, nega i e con ols,
and decon amina ion p ocedu es (Fice ola e al., 2015). S ill, he in e p e a ion o hese
unexpec ed de ec ions equi ed cau ion and con ex . Fo ins ance, eDNA de ec ion o
shad a h ee si es (chap e 2) whe e i was his o ically absen ini ially appea ed
p omising. Howe e , u he analysis con i med hese as spu ious esul s, likely
s emming om ace con amina ion o sampling e o . Simila ly, Chap e 3 e ealed 30
axa absen om his o ical da a, mos o which con ibu ed less han 1% o sequence
eads. Some o hese de ec ions likely e lec ed DNA anspo ed om ups eam
eshwa e sou ces o he adjacen ma ine en i onmen , o e en human-induced
con amina ion e.g., sewage o ood was e (Inoue e al., 2023; Jeunen e al., 2019; Polanco
e al., 2021). These cases highligh he impo ance o in e p e ing eDNA p esence wi h
ecological and en i onmen al con ex in mind.
I 's also c ucial o dis inguish be ween molecula -le el alse posi i es (e.g.,
con amina ion o lab e o ) and ecological in e ence alse posi i es, whe e DNA is
co ec ly de ec ed, bu he species may no be ac i ely using he sampled habi a (Da ling
e al., 2021). Fo example, he de ec ion o 24 pelagic species ia eDNA in es ua ies
despi e hei absence om his o ical awl da a was no necessa ily inco ec . Ra he , i
e lec ed he limi a ions o bo om awling, which p ima ily a ge s deme sal species. As
Da ling e al. (2021) emphasize communica ing his dis inc ion clea ly
only ha i wen unde ec ed by ha me hod.
2.2 Unco e ing alse nega i es
On he o he hand, alse nega i es whe e eDNA ails o de ec a species known
o be p esen can esul om low DNA concen a ions, poo assay design, incomple e
GENERAL DISCUSSION
89
e e ence lib a ies, o seasonal absence (Fice ola e al., 2015). In chap e 2, qPCR ailed
o de ec sea lamp ey a 41 si es and shad a 21 si es whe e his o ical eco ds con i med
p esence, ini ially aised he possibili y o alse nega i es ins ances whe e he species
was p esen bu wen unde ec ed by he assay. Fo sea lamp ey, dPCR success ully
de ec ed he species a 23 si es ou o 41 whe e qPCR had ailed, con i ming hese as
me hodological alse nega i es a he han ecological absence likely caused by he limi ed
sensi i i y o qPCR. Howe e , in case o shad, hese his o ically p esence si es emain
unde ec ed e en wi h dPCR. This consis en absence ac oss bo h assays sugges s a
po en ial ecological decline a he han a me hodological limi a ion, poin ing owa d a
possible ue nega i e scena io a hose loca ions. In Chap e 3, some species emained
unde ec ed by eDNA simply due o a lack o e e ence sequences, which p e en ed
iden i ica ion despi e hei DNA being p esen .
Taken oge he , hese examples unde sco e he alue o using eDNA da a in
conjunc ion wi h his o ical eco ds and o he con ex ual in o ma ion. Misin e p e a ion
can be minimized by dis inguishing be ween di e en ypes o e o s and by
unde s anding he limi a ions o bo h molecula and adi ional me hods. Ul ima ely,
eDNA should no be iewed in isola ion bu as pa o an in eg a ed moni o ing
amewo k ha balances sensi i i y wi h ecological unde s anding.
3. Beyond species de ec ion
Beyond simply ca aloguing species, his hesis explo ed how eDNA da a can be
in eg a ed in o es ua ine ecological assessmen s. Chap e 3 explo ed he easibili y o
using eDNA da a o in o m ecological s a us assessmen s, compa ing esul s wi h hose
de i ed om adi ional bo om awl su eys. The indings e ealed ha he choice o
me hod as discussed abo e can signi ican ly in luence he ecological s a us and
conclusions d awn. The di e ences in ecological s a us a e no laws, bu e lec ions o
how each me hod samples biodi e si y di e en ly, and pa icula ly how exis ing indices
in e p e eDNA-de i ed communi y da a compa ed o adi ional sou ces. Mos indices
we e o iginally designed wi h adi ional su ey da a in mind. I eDNA is o be in eg a ed
meaning ully in o hese ools, we mus conside how i s b oade de ec ion capaci y
in e ac s wi h exis ing sco ing sys ems. In e p e ing eDNA-de i ed indices equi es an
unde s anding o DNA anspo , deg ada ion, and pe sis ence, pa icula ly in dynamic
en i onmen s like es ua ies. A he same ime, hese indings o e a majo oppo uni y.
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
90
-in asi e, scalable na u e makes i well-sui ed o la ge-scale and epea able
ecosys em assessmen s (Thomsen e al., 2024). Ra he han eplacing adi ional su eys,
eDNA analysis would be seen as a complemen a y da a s eam one ha can expand and
e ine how we e alua e ecosys em condi ion. Bu his in eg a ion will equi e
ecalib a ing exis ing assessmen amewo ks, de eloping me hod-speci ic e e ence
poin s, and building con idence in molecula da a h ough con inued alida ion and c oss-
me hod compa isons (Lepage e al., 2016).
3.1 Realizing
Despi e apid ad ancemen s in eDNA echnology, i s global applica ion emains
une en. The majo i y o s udies ha e been de eloped and es ed in empe a e egions,
leading o me hodological amewo ks ha may no di ec ly ansla e o opical
ecosys ems whe e biodi e si y is no only iche bu also mo e a isk (Robson e al.,
2016).
This hesis highligh s bo h he need and he complexi y o ex ending eDNA
analysis in o opical egions. Chap e 1 p o ided a global syn hesis, e ealing how
opical coun ies, despi e being biodi e si y ho spo s and majo con ibu o s o global
ishe ies a e unde ep esen ed in eDNA esea ch. F om he inding, one o he mos
signi ican limi a ions is he lack o comp ehensi e gene ic e e ence da abases.
The e o e, e en when eDNA is success ully sequenced, he absence o ma ching ba code
da a p e en s accu a e species-le el iden i ica ion. Fo example, India s ands ou as a
signi ican playe in he global ishe ies sec o , ye i g apples wi h subs an ial gaps in i s
e e ence da abases, which signi ican ly hinde ing he applica ion o eDNA-based
biodi e si y moni o ing.
In opical aqua ic sys ems, high empe a u es, ele a ed mic obial loads, and
hyd ological u bulence in e ac o accele a e eDNA deg ada ion. As shown by Ba nes
and Tu ne (2016) and S ickle e al. (2015), hese en i onmen al s esso s signi ican ly
sho en he eDNA de ec ion window, posing unique challenges o biodi e si y
moni o ing in opical egions. Species ha a e ansien , p esen a low densi ies, o
cha ac e ized by minimal DNA shedding pose a highe isk o going unde ec ed
pa icula ly in wa m, high- u no e en i onmen s whe e deg ada ion a es a e ele a ed
(Hun e e al., 2017; Tsuji e al., 2017). This makes alse nega i es a c i ical limi a ion
GENERAL DISCUSSION
91
o eDNA moni o ing in opical and dynamic aqua ic sys ems. As demons a ed in
Chap e 2, de ec ion sensi i i y plays a pi o al ole in o e coming hese challenges. The
supe io pe o mance o molecula assay in de ec ing low-concen a ion DNA sugges s
ha mo e sensi i e molecula app oaches a e essen ial o eliable moni o ing in opical
en i onmen s. Addi ionally, hyd ological complexi y, including high sedimen loads,
seasonal low a iabili y, and s ong idal in luence can cause eDNA o be anspo ed
o e long dis ances o en apped in sedimen laye s, c ea ing spa ial misma ches be ween
whe e a species is de ec ed and whe e i is ac ually p esen . As shown in Chap e 3, such
anspo dynamics complica e species localiza ion and in e p e a ion in es ua ine
ecosys ems. These e ec s a e likely e en mo e p onounced in opical sys ems, especially
du ing monsoon seasons o wi hin highly connec ed i e ne wo ks, u he complica ing
accu a e ecological in e ence.
The lessons d awn om his hesis emphasize he need o adap a ion a he han
eplica ion when applying eDNA me hodologies ac oss di e se ecological con ex s.
While Chap e s 2 and 3 ocused on empe a e ecosys ems, hey p o ide me hodological
insigh s such as assay sensi i i y, in e p e i e igo , and he c i ical impo ance o
comp ehensi e e e ence da abases ha a e highly ele an o opical egions. These
insigh s demons a e ha eDNA moni o ing is no a one-size- i s-all solu ion, bu a he
a amewo k ha mus be ailo ed o local en i onmen al and biological condi ions. When
in eg a ed wi h he global syn hesis p esen ed in Chap e 1, he indings unde sco e he
u gency o de eloping egion-speci ic wo k lows o eDNA applica ion in opical
ecosys ems.
4. The big pic u e: ad ancing eDNA science o he
u u e
As his hesis has shown, eDNA o e s a new lens o unde s anding he way we
app oach om enhancing species de ec ion o b oadening ecological assessmen s.
While many o he di ec ions ou lined he e a e al eady being pu sued in speci ic
con ex s pa icula ly in empe a e sys ems o esea ch-in ensi e egions hey ha e ye
o be uni e sally implemen ed, s anda dized, o adap ed o he ull spec um o ecological
and policy se ings. The ollowing p io i ies a e no p esen ed as no el ideas bu as key
a eas ha equi e b oade a en ion, coo dina ion, and in es men .
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
92
4.1 Imp o e unde s anding o eDNA a e and anspo
Despi e apid g ow h in eDNA applica ions, signi ican unce ain ies emain
a ound how eDNA beha es in di e en en i onmen s. Resea ch is needed o cla i y how
long eDNA pe sis s, how a i a els, and how en i onmen al a iables (e.g.,
empe a u e, sedimen , mic obial ac i i y) in luence i s de ec abili y. Combining eDNA
esea ch wi h hyd ological, Lag angian, and sedimen anspo models will be essen ial
o imp o ing spa ial in e p e a ion and educing in e ence e o s (And uszkiewicz e al.,
2019; Pe y e al., 2024).
4.2 Enhance he quan i a i e powe o eDNA
Mos cu en eDNA applica ions ocus on p esence absence de ec ion, which
limi s hei use ulness o moni o ing popula ion ends. Fu u e wo k should es ablish
links be ween eDNA signal s eng h and species abundance o biomass. Tools such as
dPCR, occupancy modeling, and machine lea ning o e p omise bu equi e b oade
ecological alida ion. De eloping s anda dized quan i ica ion amewo ks will be key o
using eDNA in s ock assessmen s and conse a ion planning (Ya es e al., 2019).
4.3 Expand and egionalize e e ence da abases
Accu a e eDNA species iden i ica ion depends on he a ailabili y o comple e and
cu a ed gene ic e e ence da abases. In many egions pa icula ly he opics ba code
co e age is spa se. E en when sequencing is success ul, limi ed da abases esul in alse
nega i es o ambiguous de ec ions. Signi ican in es men in axon-speci ic ba coding
and egional da abase de elopmen is ounda ional o scaling eDNA moni o ing globally
(Cla e e al., 2023).
4.4 In eg a e eDNA analysis in o policy and moni o ing
amewo ks
Fo eDNA o ansi ion om academic esea ch in o en i onmen al policy, i mus
be suppo ed by o mal s anda ds, legal guidance, and egula o y in eg a ion. Cu en ly,
inconsis en me hods hinde i s use in en i onmen al epo ing and conse a ion law. As
The oux e al. (2025) a gue, s anda dized p o ocols a e c ucial o da a c edibili y,
ep oducibili y, and egula o y us .
GENERAL DISCUSSION
93
4.5 Adop au oma ion and emo e moni o ing echnologies
The u u e o eDNA lies in au oma ed, eal- ime sampling pla o ms ha in eg a e
emo e sensing and apid analysis. These inno a ions allow o b oade spa ial and
empo al co e age, ea ly de ec ion o in asi e species, and biodi e si y acking in ha d-
o- each a eas. Ad ances in senso design and au oma ed p ocessing a e al eady
unde way and will be key o scalable eDNA deploymen (P es on e al., 2023; Sepul eda
e al., 2020).
4.6 P omo e in e disciplina y and inclusi e collabo a ion
eDNA science h i es h ough collabo a ion be ween ecologis s, molecula
biologis s, da a scien is s, hyd ologis s, and local communi ies. In ol ing s akeholde s
especially hose in biodi e si y- ich bu in as uc u e-limi ed a eas can imp o e da a
co e age, educe cos s, and suppo inclusi e conse a ion. Communi y-based sampling
e o s in he Neo opics and sub-Saha an egions a e examples o his collabo a i e
u u e.
4.7 Expand owa d ecosys em-le el, mul i- ophic eDNA
assessmen s
Beyond species lis s, u u e eDNA amewo ks could assess ecosys em heal h by
analyzing mul iple ophic le els (e.g., mic obes, in e eb a es, ish, mammals) om a
single sample. This would suppo mo e holis ic ecological indica o s and o e new ways
o moni o en i onmen al change and es o a ion success.
4.8 Ad ance Global S anda diza ion o eDNA Analysis
One o he mos c i ical global needs is he ha moniza ion o eDNA me hods
ac oss ield sampling, labo a o y wo k lows, and da a analysis. Cu en ly,
me hodological inconsis ency educes he compa abili y o eDNA esul s be ween
egions, limi ing i s policy u ili y and unde mining ep oducibili y. As ou lined by he
USGS and in e na ional pa ne s, globally ecognized s anda ds co e ing QA/QC,
con amina ion con ol, assay calib a ion, and epo ing a e ounda ional o he u u e o
eDNA as a c oss-bo de moni o ing app oach (The oux e al., 2025).
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
94
CONCLUSION AND THESIS
95
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
96
The o e a ching aim o his s udy was o e alua e and ad ance he use o
en i onmen al DNA (eDNA) analysis as a p ac ical and eliable app oach o moni o ing
ish biodi e si y and assessing ecological condi ions in es ua ine ecosys ems. The s udy
assessed he me hodological pe o mance o eDNA analysis, i s ecological applicabili y,
and po en ial in eg a ion in o conse a ion and ishe ies managemen amewo ks.
Based on he syn hesis, empi ical in es iga ions, and me hodological compa isons
conduc ed h oughou he h ee co e chap e s, he ollowing conclusions we e d awn:
1) eDNA analysis p esen s signi ican oppo uni ies o opical ishe ies
managemen by p o iding a non-in asi e, cos -e ec i e app oach o ishe ies
esou ce managemen in da a-limi ed egions; howe e , challenges such as
me hodological inconsis encies, limi ed e e ence da abases, and geog aphical
biases p esen challenges o i s egion-speci ic adop ion.
2) Assay sensi i i y plays a c i ical ole in species de ec ion, pa icula ly o low-
abundance o c yp ic species. The compa ison be ween qPCR and dPCR in
de ec ing diad omous ishes e ealed ha dPCR signi ican ly imp o ed de ec ion
o sea lamp ey in low-concen a ion scena ios, unde sco ing he impo ance o
aligning assay selec ion wi h species ecology.
3) B oad-scale eDNA su eys e ealed conce ning pa e ns o species absence in
his o ically occupied habi a s ac oss 44 i e basins, especially o conse a ion-
p io i y species such as Eu opean shad and sea lamp ey. These indings suppo
e idence o popula ion declines and demons a e he alue o eDNA o long-
e m, basin-wide moni o ing.
4) eDNA me aba coding imp o ed species de ec ion by cap u ing a b oade
axonomic ange han bo om awl su eys, making i a aluable app oach o
enhancing ca chabili y es ima es and p o iding a mo e comp ehensi e assessmen
o a ge species assemblages.
5) eDNA me aba coding o e s a p omising non-in asi e app oach o con ibu ing
o es ua ine ecological assessmen indices as a complemen a he han a
eplacemen o con en ional me hods, and calib a ion e o s a e needed o
egula o y applica ions unde amewo ks like he Eu opean Wa e F amewo k
Di ec i e (WFD) o align eDNA-based biodi e si y assessmen s wi h exis ing
ecological indices.
CONCLUSION AND THESIS
97
6) Applying eDNA analyses ac oss di e en aqua ic en i onmen s con i med i s
po en ial and limi a ions, emphasizing he need o me hodological e inemen ,
including species-speci ic de ec ion biases, he in luence o sampling s a egy on
DNA eco e y, and he necessi y o imp o ed egional e e ence da abases o
enable mo e p ecise axonomic esolu ion and ecological in e p e a ion.
The conclusions eached on his hesis disse a ion allowed wo king owa ds he
s a ed hypo hesis, being he hesis ha :
o moni o ing ish biodi e si y ac oss i e ine and es ua ine sys ems. Th ough global
syn hesis, species-speci ic compa isons, and communi y-le el analyses, i a i
po en ial o complemen o enhance adi ional moni o ing app oaches p o ided ha
me hodological calib a ions, e e ence da a imp o emen and comple ion, and in eg a ion
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
104
Bi k, S., Bonne, W., Bo ja, A., B uce , S., Cou a , A., Poikane, S., Solimini, A., an de
Bund, W., Zampoukas, N., & He ing, D. (2012). Th ee hund ed ways o assess
Eu ope's su ace wa e s: An almos comple e o e iew o biological me hods o
implemen he Wa e F amewo k Di ec i e. Ecological Indica o s, 18, 31-41.
h ps://doi.o g/10.1016/j.ecolind.2011.10.009
Blai , N. E., & Alle , R. C. (2012). The a e o e es ial o ganic ca bon in he ma ine
en i onmen . Annual e iew o ma ine science, 4, 401-423.
h ps://doi.o g/10.1146/annu e -ma ine-120709-142717
Boha a, K., Joshi, P., Acha ya, K. P., & Ramena, G. (2024). Eme ging echnologies
e olu ionising disease diagnosis and moni o ing in aqua ic animal heal h.
Re iews in Aquacul u e, 16(2), 836-854. h ps://doi.o g/10.1111/ aq.12870
Bohmann, K., E ans, A., Gilbe , M. T. P., Ca alho, G. R., C ee , S., Knapp, M., Yu,
D. W., & de B uyn, M. (2014). En i onmen al DNA o wildli e biology and
biodi e si y moni o ing. T ends Ecol E ol, 29(6), 358-367.
h ps://doi.o g/10.1016/j. ee.2014.04.003
Bolge , A. M., Lohse, M., & Usadel, B. (2014). T immoma ic: a lexible imme o
Illumina sequence da a. Bioin o ma ics, 30(15), 2114-2120.
h ps://doi.o g/10.1093/bioin o ma ics/b u170
Bo ja, A., Ada aga, I., Bald, J., Belzunce-Sega a, M. J., C uz, I., F anco, J., Ga mendia,
J. M., La e a, J., Laza-Ma ínez, A., & Manzanos, A. (2025). Ma ine Biodi e si y
and En i onmen al Da a: An AI-Ready, Open Da ase om he long e m (1995-
2023) Basque Coun y Moni o ing Ne wo k. F on ie s in Ocean Sus ainabili y, 2,
1528837. h ps://doi.o g/10.3389/ ocsu.2024.1528837
Bo ja, A., Ellio , M., Ande sen, J. H., Ca doso, A. C., Ca s ensen, J., Fe ei a, J. G.,
Heiskanen, A. S., Ma ques, J. C., Ne o, J. M., Teixei a, H., Uusi alo, L., Uya a,
M. C., & Zampoukas, N. (2013). Good En i onmen al S a us o ma ine
ecosys ems: Wha is i and how do we know when we ha e a ained i ? Ma Pollu
Bull, 76(1-2), 16-27. h ps://doi.o g/10.1016/j.ma polbul.2013.08.042
Bo ja, A., F anco, J., Valencia, V., Bald, J., Muxika, I., Belzunce, M. J., & Solaun, O.
(2004). Implemen a ion o he Eu opean wa e amewo k di ec i e om he
REFERENCES
105
Basque coun y (no he n Spain): a me hodological app oach. Ma Pollu Bull,
48(3-4), 209-218. h ps://doi.o g/10.1016/j.ma polbul.2003.12.001
Bo ja, A., Lanzén, A., & Muxika, I. (2024). DNA-based ma ine ben hic assessmen
me hods can pe o m as mo phological ones, bu an in e calib a ion is needed.
Ecological Indica o s, 167, 112638.
h ps://doi.o g/10.1016/j.ecolind.2024.112638
Bo olus, A. (2008). E o cascades in he biological sciences: The unwan ed
consequences o using bad axonomy in ecology. Ambio, 37(2), 114-118.
h ps://doi.o g/10.1579/0044-7447(2008)37[114:Eci bs]2.0.Co;2
Bowe s, H., Pochon, X., on Ammon, U., Gemmell, N., S an on, J.-A., Jeunen, G.-J.,
She man, C., & Zaiko, A. (2021). Towa ds he Op imiza ion o eDNA/eRNA
Sampling Technologies o Ma ine Biosecu i y Su eillance. Wa e , 13(8), 1113.
h ps://doi.o g/10.3390/w13081113
Boye , S., W a en, S. D., Holyoake, A., Abdelk im, J., & C uickshank, R. H. (2013).
Using Nex -Gene a ion Sequencing o Analyse he Die o a Highly Endange ed
Land Snail (Powelliphan a augus a) Feeding on Endemic Ea hwo ms. PLoS
ONE, 8(9), e75962. h ps://doi.o g/10.1371/jou nal.pone.0075962
B acken, F. S. A., Rooney, S. M., Kelly-Quinn, M., King, J. J., & Ca lsson, J. (2019).
Iden i ying spawning si es and o he c i ical habi a in lo ic sys ems using eDNA
"snapsho s": A case s udy using he sea lamp ey Pe omyzon ma inus L. Ecol E ol,
9(1), 553-567. h ps://doi.o g/10.1002/ece3.4777
R. H. (2022). En i onmen al DNA de ec ion and abundance es ima es compa able
o con en ional me hods o h ee eshwa e la al species a a powe plan
discha ge. En i onmen al DNA, 4(3), 700 714. h ps://doi.o g/10.1002/edn3.286
B adshaw, C. J., Sodhi, N. S., & B ook, B. W. (2009). T opical u moil: A biodi e si y
agedy in p og ess. F on ie s in Ecology and he En i onmen , 7(2), 79 87.
h ps://doi.o g/10.1890/070193
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
106
B önma k, C., Hul hén, K., Nilsson, P. A., Sko , C., Hansson, L.-A., B ode sen, J., &
Chapman, B. B. (2014). The e and back again: Mig a ion in eshwa e ishes.
Canadian Jou nal o Zoology, 92(6), 467 479. h ps://doi.o g/10.1139/cjz-2012-
0277
B uce, K., Blackman, R., Bou la , S. J., Hells öm, A. M., Bakke , J., Bis a, I., Bohmann,
K., Bouchez, A., B ys, R., Cla k, K., Elb ech , V., Fazi, S., Fonseca, V., Hän ling,
K. (2021). A p ac ical guide o DNA-based me hods o biodi e si y assessmen .
Penso Publishe s. h ps://doi.o g/10.3897/ab.e68634
B ys, R., Hal mae en, D., Ney inck, S., Mau isseau, Q., Auwe x, J., Swee , M., &
Me geay, J. (2021). Reliable eDNA de ec ion and quan i ica ion o he Eu opean
wea he loach ( Misgu nus ossilis ). Jou nal o Fish Biology, 98(2), 399 414.
h ps://doi.o g/10.1111/j b.14315
Bu ian, A., B uce, K., To ela, E., Bakke , J., Balcells, L., Benne , R., Cho deka , S.,
A., Sida , N., Simbine, L., Ready, J., Tang, C., & Mau isseau, Q. (2023). Me ging
wo
Molecula Ecology Resou ces, 23(7), 1641 1655. h ps://doi.o g/10.1111/1755-
0998.13839
Bylemans, J., Fu lan, E. M., Ha dy, C. M., McGu ie, P., Lin e mans, M., & Gleeson, D.
M. (2017). An en i onmen al based me hod o moni o ing spawning
ac i i y: A case s udy, using he endange ed Macqua ie pe ch ( Macqua ia
aus alasica ). Me hods in Ecology and E olu ion, 8(5), 646 655.
h ps://doi.o g/10.1111/2041-210X.12709
REFERENCES
107
Cab al, H. N., Bo ja, A., Fonseca, V. F., Ha ison, T. D., Teiche , N., Lepage, M., &
Leal, M. C. (2022). Fishes and Es ua ine En i onmen al Heal h. In Fish and
Fishe ies in Es ua ies (pp. 332-379).
h ps://doi.o g/h ps://doi.o g/10.1002/9781119705345.ch6
An
in e eb a e s omach's iew on e eb a e ecology: Ce ain in e eb a es could be
aspec s o e eb a e ecology. BioEssays, 35(11), 1004-1013.
h ps://doi.o g/10.1002/bies.201300060
Ve ical s a i ica ion o en i onmen al DNA in he open ocean cap u es
Limnology and
Oceanog aphy Le e s, 6(6), 339 347. h ps://doi.o g/10.1002/lol2.10213
Can e a, I., Cille os, K., Valen ini, A., Ce dan, A., Dejean, T., I iba , A., Tabe le , P.,
Vigou oux, R., & B osse, S. (2019). Op imizing en i onmen al DNA sampling
e o o ish in en o ies in opical s eams and i e s. Sci Rep, 9.
h ps://doi.o g/10.1038/s41598-019-39399-5
Can e a, I., Cille os, K., Valen ini, A., Ce dan, A., Dejean, T., I iba , A., Tabe le , P.,
Vigou oux, R., & B osse, S. (2019). Op imizing en i onmen al DNA sampling
e o o ish in en o ies in opical s eams and i e s. Scien i ic Repo s, 9(1),
3085. h ps://doi.o g/10.1038/s41598-019-39399-5
Capo, E., Spong, G., Königsson, H., & Bys öm, P. (2020). E ec s o il a ion me hods
and wa e olume on he quan i ica ion o b own ou (Salmo u a) and A c ic
cha (Sal elinus alpinus) eDNA concen a ions ia d ople digi al PCR.
En i onmen al DNA, 2(2), 152-160. h ps://doi.o g/10.1002/edn3.52
Ca øe, C., & Bohmann, K. (2020). Tags eady: A me aba coding lib a y p epa a ion
p o ocol o a oid alse assignmen o sequences o samples. Mol Ecol Resou ,
20(6), 1620-1631. h ps://doi.o g/10.1111/1755-0998.13227
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
108
J , P. M. (2022). E iciency o eDNA and iDNA in assessing e eb a e di e si y
and i s abundance. Mol Ecol Resou , 22(4), 1262-1273.
h ps://doi.o g/10.1111/1755-0998.13543
Cas añeda, R. A., Van Nyna en, A., C ookes, S., Ellende , B. R., Hea h, D. D., MacIsaac,
H. J., Mand ak, N. E., & Weyl, O. L. F. (2020). De ec ing Na i e F eshwa e
Fishes Using No el Non-in asi e Me hods. F on ie s in En i onmen al Science,
8, 29. h ps://doi.o g/10.3389/ en s.2020.00029
Caswell, N. M., Pe e son, D. L., Manny, B. A., & Kennedy, G. W. (2004). Spawning by
lake s u geon (Acipense ul escens) in he De oi Ri e . Jou nal o Applied
Ich hyology, 20(1), 1 6. h ps://doi.o g/10.1111/j.1439-0426.2004.00499.x
and abio ic ac o s on he p oduc ion and deg ada ion o ish en i onmen al DNA:
An expe imen al e alua ion. En i onmen al DNA, 4(2), 453 468.
h ps://doi.o g/10.1002/edn3.266
CEPF. (2016). Annual Repo 2016 (p. 66). C i ical Ecosys em Pa ne ship Fund.
h ps://www.cep .ne /si es/de aul / iles/CEPF-FY16-Annual-Repo .pd
Chand a, K., Raguna han, C., & Sheela, S. (2020). Animal disco e ies 2019: New species
and new eco ds. Zoological Su ey o India, Kolka a, 1 184.
Chapa o-Ped aza, P. C., & de Roos, A. M. (2019). En i onmen al change e ec s on li e-
his o y ai s and popula ion dynamics o anad omous ishes [Resea ch Suppo ,
Non-U.S. Go ' ]. J Anim Ecol, 88(8), 1178-1190. h ps://doi.o g/10.1111/1365-
2656.13010
Chu, C., Mand ak, N. E., & Minns, C. K. (2005). Po en ial impac s o clima e change on
he dis ibu ions o se e al common and a e eshwa e ishes in Canada. Di e si y
REFERENCES
109
and Dis ibu ions, 11(4), 299-310. h ps://doi.o g/10.1111/j.1366-
9516.2005.00153.x
Chucholl, F., Fiolka, F., Segelbache , G., & Epp, L. S. (2021). EDNA De ec ion o Na i e
and In asi e C ay ish Species Allows o Yea -Round Moni o ing and La ge-
Scale Sc eening o Lo ic Sys ems. F on ie s in En i onmen al Science, 9, 639380.
h ps://doi.o g/10.3389/ en s.2021.639380
Ciannelli, L., Fauchald, P., Chan, K. S., Agos ini, V. N., & Dingsø , G. E. (2008). Spa ial
ishe ies ecology: Recen p og ess and u u e p ospec s. Jou nal o Ma ine
Sys ems, 71, 223-236. h ps://doi.o g/10.1016/j.jma sys.2007.02.031
Cille os, K., Valen ini, A., Alla d, L., Dejean, T., E ienne, R., G enouille , G., I iba , A.,
Tabe le , P., Vigou oux, R., & B osse, S. (2019). Unlocking biodi e si y and
(eDNA): A es wi h Guianese eshwa e ishes. Molecula Ecology Resou ces,
19(1), 27 46. h ps://doi.o g/10.1111/1755-0998.12900
(2023). An au oma ed wo k low o assess comple eness and cu a e GenBank o
en i onmen al DNA me aba coding: The ma ine ish assemblage as case s udy.
En i onmen al DNA, 5(4), 634-647. h ps://doi.o g/10.1002/edn3.433
Clemens, B. J., Ha is, J. E., S a ce ich, S. J., E ans, T. M., Skalicky, J. J., Nea e, F., &
Lampman, R. T. (2022). Sampling me hods and su ey designs o la al lamp eys.
No h Ame ican Jou nal o Fishe ies Managemen , 42(2), 455-474.
h ps://doi.o g/10.1002/na m.10762
CMFRI, K. (2023). Ma ine Fish S ock S a us o India, 2022 (Rep in 2023). In: ICAR-
Cen al Ma ine Fishe ies Resea ch Ins i u e.
Collins, R. A., Bakke , J., Wangens een, O. S., So o, A. Z., Co igan, L., Sims, D. W.,
Genne , M. J., & Ma iani, S. (2019). Non-speci ic ampli ica ion comp omises
en i onmen al DNA me aba coding wi h COI. Me hods in Ecology and
E olu ion, 10(11), 1985-2001. h ps://doi.o g/10.1111/2041-210x.13276
Colmena es, G. M. G., Mon es, A. J. G., Ha ms-Tuohy, C. A., & Schizas, N. V. (2023).
Using eDNA sampling o species-speci ic ish de ec ion in opical oceanic
samples: limi a ions and ecommenda ions o u u e use. Pee J, 11, e14810.
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
110
Cos ello, C., O ando, D., Hilbo n, R., Gaines, S. D., Deschenes, O., & Les e , S. E.
Science,
338(6106), 517 520. h ps://doi.o g/10.1126/science.1223389
C ookes, S., Hee , T., Cas añeda, R. A., Mand ak, N. E., Hea h, D. D., Weyl, O. L. F.,
MacIsaac, H. J., & Foxc o , L. C. (2020). Moni o ing he sil e ca p in asion in
A ica: A case s udy using en i onmen al DNA (eDNA) in dange ous wa e sheds.
NeoBio a, 56, 31 47. h ps://doi.o g/10.3897/neobio a.56.47475
Cuche ousse , J., & Olden, J. D. (2011). Ecological Impac s o Nonna i e F eshwa e
Fishes. Fishe ies, 36(5), 215 230.
h ps://doi.o g/10.1080/03632415.2011.574578
Dahanuka , N., Diweka , M., & Painganka , M. (2011). Redisco e y o he h ea ened
Wes e n Gha s endemic siso id ca ish Glyp o ho ax poonaensis (Teleos ei:
Silu i o mes: Siso idae). Jou nal o Th ea ened Taxa, 3(7), 1885 1898.
h ps://doi.o g/10.11609/JoTT.o2663.1885-98
Das, M., & Hassan, M. (2008). S a us o ish mig a ion and passes wi h special e e ence
o India. ICAR-CIFRI.
Da ison, P. I., Falcou-P é ol, M., Copp, G. H., Da ies, G. D., Vilizzi, L., & C éach, V.
(2019). Is i absen o is i p esen ? De ec ion o a non-na i e ish o in o m
managemen decisions using a new highly-sensi i e eDNA p o ocol. Biological
In asions, 21(8), 2549-2560. h ps://doi.o g/10.1007/s10530-019-01993-z
De Sil a, H. G., & Medellín, R. A. (2001). E alua ing comple eness o species lis s o
conse a ion and mac oecology: a case s udy o Mexican land bi ds. Conse a ion
Biology, 15(5), 1384-1395. h p://dx.doi.o g/10.1111/j.1523-1739.2001.00177.x
REFERENCES
111
Deine , K., Lopez, J., Bou ne, S., Holman, L., Seymou , M., G ey, E. K., Lacou siè e, A.,
Li, Y., Renshaw, M. A., P ende , M. E., Rius, M., Be na chez, L., & Lodge, D.
M. (2018). Op imising he de ec ion o ma ine axonomic ichness using
en i onmen al DNA me aba coding: The e ec s o il e ma e ial, po e size and
ex ac ion me hod. Me aba coding and Me agenomics, 2, e28963.
h ps://doi.o g/10.3897/mbmg.2.28963
Deine , K., Walse , J.-C., Mächle , E., & Al e ma , F. (2015). Choice o cap u e and
ex ac ion me hods a ec de ec ion o eshwa e biodi e si y om en i onmen al
DNA. Biological Conse a ion, 183, 53 63.
h ps://doi.o g/10.1016/j.biocon.2014.11.018
Deine , K., Yamanaka, H., & Be na chez, L. (2021). The u u e o biodi e si y
moni o ing and conse a ion u ilizing en i onmen al DNA. En i onmen al DNA,
3(1), 3 7. h ps://doi.o g/10.1002/edn3.178
Des oche s, A., McIn i e, E. J., Cumming, S. G., Nowak, J., & Sha ma, S. (2010). False
nega i es A alse p oblem in s udies o habi a selec ion? Ideas in Ecology and
E olu ion, 3. h ps://doi.o g/10.4033/iee.2010.3.5.n
Dhee, A h eya, V., Linnell, J. D. C., Shi akuma , S., & Dhiman, S. P. (2019). The leopa d
ha lea n om he ca and o he na a i es o ca ni o e human coexis ence in
no he n India. People and Na u e, 1(3), 376 386.
h ps://doi.o g/10.1002/pan3.10039
Diana, J. S., Hanchin, P., & Popo , N. (2015). Mo emen pa e ns and spawning si es o
muskellunge Esox masquinongy in he An im chain o lakes, Michigan.
En i onmen al Biology o Fishes, 98(3), 833 844.
h ps://doi.o g/10.1007/s10641-014-0319-7
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
112
Díaz-Abad, L., Bacco-Mannina, N., Madei a, F. M., Nei a, J., Ai es, T., Se ao, E. A.,
Regalla, A., Pa ício, A. R., & F ade, P. R. (2022). eDNA me aba coding o die
analyses o g een sea u les (Chelonia mydas). Ma ine Biology, 169(1), 18.
h ps://doi.o g/10.1007/s00227-021-04002-x
Díaz-Fe guson, E. E., & Moye , G. R. (2014). His o y, applica ions, me hodological
issues and pe spec i es o he use en i onmen al DNA (eDNA) in ma ine and
eshwa e en i onmen s. Re is a de biologia opical, 62(4), 1273-1284.
h p://dx.doi.o g/10.15517/ b . 62i4.13231
Dickie, I. A., Boye , S., Buckley, H. L., Duncan, R. P., Ga dne , P. P., Hogg, I. D.,
Holdaway, R. J., Lea , G., Makiola, A., Mo ales, S. E., Powell, J. R., & Wea e ,
L. (2018). Towa ds obus and epea able sampling me hods in EDNA
s udies. Molecula Ecology Resou ces, 18(5), 940 952.
h ps://doi.o g/10.1111/1755-0998.12907
Dingle, H., & D ake, V. A. (2007). Wha Is Mig a ion? BioScience, 57(2), 113 121.
h ps://doi.o g/10.1641/B570206
Dju huus, A., Closek, C. J., Kelly, R. P., Pi z, K. J., Michisaki, R. P., S a ks, H. A., Walz,
K. R., And uszkiewicz, E. A., Olesin, E., Hubba d, K., Mon es, E., O is, D.,
Mulle -Ka ge , F. E., Cha ez, F. P., Boehm, A. B., & B ei ba , M. (2020).
En i onmen al DNA e eals seasonal shi s and po en ial in e ac ions in a ma ine
communi y. Na u e Communica ions, 11(1), 254. h ps://doi.o g/10.1038/s41467-
019-14105-1
Dodds, W. K., Pe kin, J. S., & Ge ken, J. E. (2013). Human impac on eshwa e
ecosys em se ices: a global pe spec i e. En i on Sci Technol, 47(16), 9061-9068.
h ps://doi.o g/10.1021/es4021052
REFERENCES
113
Doi, H., Uchii, K., Takaha a, T., Ma suhashi, S., Yamanaka, H., & Minamo o, T. (2015).
Use o D ople Digi al PCR o Es ima ion o Fish Abundance and Biomass in
En i onmen al DNA Su eys. PLOS ONE, 10(3), e0122763.
h ps://doi.o g/10.1371/jou nal.pone.0122763
D ake, L. E., Cu , J. P., Young, R. E., Ma chbank, A., Chadwick, E. A., & Symondson,
W. O. C. (2021). An assessmen o minimum sequence copy h esholds o
iden i ying and educing he p e alence o a e ac s in die a y me aba coding
da a. Me hods in Ecology and E olu ion, 13(3), 694-710.
h ps://doi.o g/10.1111/2041-210x.13780
Dub euil, T., Baud y, T., Mau isseau, Q., A qué, A., Cou y, C., Delaunay, C., Swee ,
M., & G andjean, F. (2022). The de elopmen o ea ly moni o ing ools o de ec
aqua ic in asi e species: eDNA assay de elopmen and he case o he a mo ed
ca ish Hypos omus obinii. En i onmen al DNA, 4(2), 349-362.
h ps://doi.o g/10.1002/edn3.260
Dully, V., Ballie , H., F ühe, L., Däume , M., Thielen, A., Gallie, S., Be ill, I., & S oeck,
T. (2021). Robus ness, sensi i i y and ep oducibili y o eDNA me aba coding as
an en i onmen al biomoni o ing ool in coas al salmon aquacul u e An in e -
labo a o y s udy. Ecological Indica o s, 121, 107049.
h ps://doi.o g/10.1016/j.ecolind.2020.107049
Dussex, N., Robe son, B. C., Salis, A. T., Kalinin, A., Bes , H., & Gemmell, N. J. (2016).
Low Spa ial Gene ic Di e en ia ion Associa ed wi h Rapid Recoloniza ion in he
New Zealand Fu Seal A c ocephalus o s e i. Jou nal o He edi y, 107(7), 581
592. h ps://doi.o g/10.1093/jhe ed/esw056
Edga , R. C., Haas, B. J., Clemen e, J. C., Quince, C., & Knigh , R. (2011). UCHIME
imp o es sensi i i y and speed o chime a de ec ion. Bioin o ma ics, 27(16),
2194-2200. h ps://doi.o g/10.1093/bioin o ma ics/b 381
Eichmille , J. J., Bes , S. E., & So ensen, P. W. (2016). E ec s o Tempe a u e and
T ophic S a e on Deg ada ion o En i onmen al DNA in Lake Wa e .
En i onmen al Science & Technology, 50(4), 1859 1867.
h ps://doi.o g/10.1021/acs.es .5b05672
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
120
Hogga h, D. D. (2006). S ock assessmen o ishe y managemen : A amewo k guide o
he s ock assessmen ools o he ishe ies managemen and science p og amme.
Food & Ag icul u e O g.
Robson, H. L. A., S ugnell, J. M., Bu ows, D., & Je y, D. R. (2020). Enhancing
opical conse a ion and ecology esea ch wi h aqua ic en i onmen al DNA
me hods: An in odu Animal
Conse a ion, 23(6), 632 645. h ps://doi.o g/10.1111/ac .12583
Hu e , J. R., Kop i nika , J., Johnson, P. T. J., & Whya d, S. (2015). De elopmen and
applica ion o an eDNA me hod o de ec and quan i y a pa hogenic pa asi e in
aqua ic ecosys ems. Ecological Applica ions, 25(4), 991 1002.
h ps://doi.o g/10.1890/14-1530.1
Huyghe, C. E. T., Ae s, D. N., Heindle , F. M., Kmen o á, N., Mushagalusa Ci huza, D.,
Volckae , F. A. M., Masilya Mulungula, P., & De Keyze , E. L. R. (2023).
Oppo unis ic eeding habi s o wo A ican eshwa e clupeid ishes: DNA
me aba coding un a els spa ial di e ences in die and mic obiome, and iden i ies
new p ey axa. Hyd obiologia, 850(17), 3777 3796.
h ps://doi.o g/10.1007/s10750-023-05267-7
ICAR-NBFGR. (2016). Guidelines o Managemen o Fish Gene ic Resou ces in India.
ICARNa ional Bu eau o Fish Gene ic Resou ces, Lucknow, India.
h ps://www.nb g . es.in/si e/w i e eadda a/si eCon en /FGR-
Guidelines_NBFGR.pd
ICES. (2003). Repo o he wo king g oup on ish ecology (WGFE). ICES CM
2003/G:04, 113. h ps://doi.o g/10.17895/ices.pub.9744
Inoue, Y., Miya a, K., Yamane, M., & Honda, H. (2023). En i onmen al Nucleic Acid
Pollu ion: Cha ac e iza ion o Was ewa e Gene a ing False Posi i es in
Molecula Ecological Su eys. ACS ES&T Wa e , 3(3), 756-764.
h ps://doi.o g/10.1021/acses wa e .2c00542
REFERENCES
121
Ip, J. C. H., Loke, H. X., Yiu, S. K. F., Zhao, M., Li, Y., Lin, Y., How, C. M., Mo, J.,
Me aba coding Su eys Re eal Highly Di e se Ve eb a e and C us acean
Communi ies: A Case S udy in an U banized Sub opical Es ua y.
En i onmen al DNA, 6(6), e70031. h ps://doi.o g/10.1002/edn3.70031
IPCC. (2019). Clima e change and land. h ps://www.ipcc.ch/ epo /s ccl/
IUCN. (2016). A Global S anda d o he Iden i ica ion o Key Biodi e si y A eas
(Ve sion 1.0. Fi s Edi ion, p. 46). IUCN.
IUCN. (2021). The IUCN Red Lis o Th ea ened Species 2021.
h ps://www.iucn edlis .o g
Jacobsen, Á., Vang, A., Sal e , I., Juul-Pede sen, T., S einsson, S., Pampoulie, C.,
Wangens een, O., P æbel, K., Mikalsen, S.-O., & Dju huus, A. (2023).
Pe spec i es on implemen a ion o eDNA me hods in No heas A lan ic ma ine
moni o ing: A basis o esea che s and s akeholde s o discuss challenges and
ambi ions. No dic Council o Minis e s.
me aba coding e eals di e se die o he h ee-spined s ickleback in a coas al
ecosys em. PLOS ONE, 12(10), e0186929.
h ps://doi.o g/10.1371/jou nal.pone.0186929
Jane, S. F., Wilcox, T. M., McKel ey, K. S., Young, M. K., Schwa z, M. K., Lowe, W.
H., Le che , B. H., & Whi eley, A. R. (2015). Dis ance, low and PCR inhibi ion:
E DNA dynamics in wo headwa e s eams. Molecula Ecology Resou ces, 15(1),
216 227. h ps://doi.o g/10.1111/1755-0998.12285
Jena, J. K., & Gopalak ishnan, A. (2012). Aqua ic Biodi e si y Managemen in India.
P oceedings o he Na ional Academy o Sciences, India Sec ion B: Biological
Sciences. h ps://doi.o g/10.1007/s40011-012-0108-z
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
122
Jenne jahn, T. C., & Mi chell, S. B. (2013). P essu es, s esses, shocks and ends in
es ua ine ecosys ems An in oduc ion and syn hesis. Es ua ine, coas al and
shel science, 130, 1-8. h ps://doi.o g/10.1016/j.ecss.2013.07.008
Je de, C. L. (2021). Can we manage ishe ies wi h he inhe en unce ain y om eDNA?
J Fish Biol, 98(2), 341-353. h ps://doi.o g/10.1111/j b.14218
Je de, C. L., Mahon, A. R., Campbell, T., McEl oy, M. E., Pin, K., Child ess, J. N.,
A ms ong, M. N., Zehnp ennig, J. R., Kelson, S. J., Koning, A. A., Ngo , P. B.,
Nuon, V., So, N., Chand a, S., & Hogan, Z. S. (2021). A e Gene ic Re e ence
Lib a ies Su icien o En i onmen al DNA Me aba coding o Mekong Ri e
Basin Fish? Wa e , 13(13), 1767. h ps://doi.o g/10.3390/w13131767
de ec ion o a e aqua ic species using en i onmen al DNA. Conse a ion le e s,
4(2), 150-157. h ps://doi.o g/10.1111/j.1755-263X.2010.00158.x
Jeunen, G. J., Knapp, M., Spence , H. G., Lama e, M. D., Taylo , H. R., S a , M.,
Bunce, M., & Gemmell, N. J. (2019). En i onmen al DNA (eDNA)
me aba coding e eals s ong disc imina ion among di e se ma ine habi a s
connec ed by wa e mo emen . Mol Ecol Resou , 19(2), 426-438.
h ps://doi.o g/10.1111/1755-0998.12982
Jiang, H., Ahn, H., & Li, X. (2022). G oup Tes ing wi h Conside a ion o he Dilu ion
E ec . Ma hema ics, 10(3), 497. h ps://doi.o g/10.3390/ma h10030497
Jo, H., Ven u a, M., Vidal, N., Gim, J., Buchaca, T., Ba mu a, L. A., Jeppesen, E., & Joo,
G. (2016). Disco e ing hidden biodi e si y: The use o complemen a y
moni o ing o ish die based on DNA ba coding in eshwa e ecosys ems.
Ecology and E olu ion, 6(1), 219 232. h ps://doi.o g/10.1002/ece3.1825
Joshi, K., Bashee , V., Kuma , A., S i as a a, S., Sahu, V., & Lal, K. (2021). Alien ish
species in open wa e s o India: Appea ance, es ablishmen and impac s. Indian
Jou nal o Animal Sciences, 91(3), 167 173.
Kawa o, M., Yoshida, T., Miya, M., Tsuchida, S., Nagano, Y., Nomu a, M., Yabuki, A.,
Fujiwa a, Y., & Fujiku a, K. (2021). Op imiza ion o en i onmen al DNA
ex ac ion and ampli ica ion me hods o me aba coding o deep-sea ish.
Me hodsX, 8, 101238. h ps://doi.o g/10.1016/j.mex.2021.101238
REFERENCES
123
Kea se, M., Moi , R., Wilson, A., S ones-Ha as, S., Cheung, M., S u ock, S., Bux on,
S., Coope , A., Ma kowi z, S., Du an, C., Thie e , T., Ash on, B., Mein jes, P., &
D ummond, A. (2012). Geneious Basic: An in eg a ed and ex endable desk op
so wa e pla o m o he o ganiza ion and analysis o sequence da a.
Bioin o ma ics, 28(12), 1647 1649.
h ps://doi.o g/10.1093/bioin o ma ics/b s199
Kelly, F. L., & King, J. J. (2001). A e iew o he ecology and dis ibu ion o h ee
lamp ey species, Lampe a lu ia ilis (L.), Lampe a plane i (Bloch) and
Pe omyzon ma inus (L.): a con ex o conse a ion and biodi e si y
conside a ions in I eland. biology and en i onmen : P oceedings o he Royal I ish
Academy,
King, A. C., K ieg, R., Wes on, A., & Zenke , A. K. (2022). Using eDNA o
simul aneously de ec he dis ibu ion o na i e and in asi e c ay ish wi hin an
en i e coun y. Jou nal o En i onmen al Managemen , 302, 113929.
h ps://doi.o g/10.1016/j.jen man.2021.113929
Adap i e managemen o an en i onmen al wa e ing e en o enhance na i e ish
spawning and ec ui men : En i onmen al low managemen o na i e ish
b eeding. F eshwa e Biology, 55(1), 17 31. h ps://doi.o g/10.1111/j.1365-
2427.2009.02178.x
King, J., Ma nell, F., Kings on, N., Rosell, R., Boylan, P., Ca ey, J., Fi zPa ick, Ú.,
I eland ed lis no. 5: amphibians,
ep iles & eshwa e ish (Na ional Pa ks and Wildli e Se ice, Depa men o
A s, He i age and he Gael ach , Dublin, I eland, Issue.
Ki mani, S. (2015). A Use F iendly App oach o Design and Economic Analysis o
S andalone SPV Sys em. Sma G id and Renewable Ene gy, 06(04), 67-74.
h ps://doi.o g/10.4236/sg e.2015.64007
Ki sch, J. E., Day, J. L., Pe e son, J. T., & Fulle on, D. K. (2018). Fish
Misiden i ica ion and Po en ial Implica ions o Moni o ing Wi hin he San
F ancisco Es ua y, Cali o nia. Jou nal o Fish and Wildli e Managemen , 9(2),
467-485. h ps://doi.o g/10.3996/032018-j wm-020
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
124
Ki ane, A., Kleye , H., & Deine , K. (2023). So ing s a es o en i onmen al DNA:
dissol ed, and adso bed s a es o eDNA. En i onmen al DNA, 5(3), 582-596.
h ps://doi.o g/10.1002/edn3.417
Klymus, K. E., Me kes, C. M., Allison, M. J., Goldbe g, C. S., Helbing, C. C., Hun e ,
M. E., Jackson, C. A., Lance, R. F., Mangan, A. M., Mon oe, E. M., Piaggio, A.
J., S okdyk, J. P., Wilson, C. C., & Rich e , C. A. (2020). Repo ing he limi s o
de ec ion and quan i ica ion o en i onmen al DNA assays. En i onmen al DNA,
2(3), 271 282. h ps://doi.o g/10.1002/edn3.29
Klymus, K. E., Rich e , C. A., Chapman, D. C., & Pauke , C. (2015). Quan i ica ion o
eDNA shedding a es om in asi e bighead ca p Hypoph halmich hys nobilis
and sil e ca p Hypoph halmich hys moli ix. Biological Conse a ion, 183, 77
84. h ps://doi.o g/10.1016/j.biocon.2014.11.020
Knigh , J. D. M. (2010). In asi e o namen al ish: A po en ial h ea o aqua ic
biodi e si y in peninsula India. Jou nal o Th ea ened Taxa, 2(2), 700 704.
h ps://doi.o g/10.11609/JoTT.o2179.700-4
Ko, H.-L., Wang, Y.-T., Chiu, T.-S., Lee, M.-A., Leu, M.-Y., Chang, K.-Z., Chen, W.-
Y., & Shao, K.-T. (2013). E alua ing he Accu acy o Mo phological
Iden i ica ion o La al Fishes by Applying DNA Ba coding. PLoS ONE, 8(1),
e53451. h ps://doi.o g/10.1371/jou nal.pone.0053451
Kos e , W. M., Dawson, D. R., Mo ongiello, J. R., & C ook, D. A. (2013). Spawning
season mo emen s o Macqua ie pe ch (Macqua ia aus alasica) in he Ya a
Ri e , Vic o ia. Aus alian Jou nal o Zoology, 61(5), 386.
h ps://doi.o g/10.1071/ZO13054
K i ze , J. P., Hall, C. I., Hoppe, B., Ogden, C., & Cou nane, J. M. (2022). Managing
Small Fish a La ge Scales: The Eme gence o Regional Policies o Ri e He ing
in he Eas e n Uni ed S a es [A icle]. Fishe ies, 47(10), 435-445.
h ps://doi.o g/10.1002/ sh.10802
Kuma , G., Fa ell, E., Reaume, A. M., Eble, J. A., & Gai he , M. R. (2022). One size
sampling. En i onmen al DNA, 4(1), 167 180. h ps://doi.o g/10.1002/edn3.235
REFERENCES
125
Kuma , G., Reaume, A. M., Fa ell, E., & Gai he , M. R. (2022). Compa ing eDNA
me aba coding p ime s o assessing ish communi ies in a biodi e se es ua y.
PLOS ONE, 17(6), e0266720. h ps://doi.o g/10.1371/jou nal.pone.0266720
Kwong, S. L. T., Villaco a-Ra h, C., Doyle, J., & U hicke, S. (2021). Quan i ying
shedding and deg ada ion a es o en i onmen al DNA (eDNA) om Paci ic
c own-o - ho ns seas a (Acan has e c . Sola is). Ma ine Biology, 168(6), 85.
h ps://doi.o g/10.1007/s00227-021-03896-x
Lacou siè e-Roussel, A., Cô é, G., Lecle c, V., & Be na chez, L. (2016). Quan i ying
ela i e ish abundance wi h eDNA: A p omising ool o ishe ies managemen .
Jou nal o Applied Ecology, 53(4), 1148 1157. h ps://doi.o g/10.1111/1365-
2664.12598
Deine , K., Lodge, D. M., He nandez, C., Leduc, N., & Be na chez, L. (2018).
eDNA me aba coding as a new su eillance app oach o coas al A c ic
biodi e si y. Ecology and E olu ion, 8(16), 7763 7777.
h ps://doi.o g/10.1002/ece3.4213
abundance and biomass om eDNA concen a ions: a iabili y among cap u e
me hods and en i onmen al condi ions. Mol Ecol Resou , 16(6), 1401-1414.
h ps://doi.o g/10.1111/1755-0998.12522
Lak a, W., Sa ka , U., Gopalak ishnan, A., & Gopalak ishnan, A. (2010). Th ea ened
eshwa e ishes o India (p. 25). Na ional Bu eau o Fish Gene ic Resou ces.
h p://ep in s.cm i.o g.in/11797/1/AGKN_2010_Ka hi _Th ea ened%20F eshw
a e %20Fishes%20o %20India_NBFGR.pd
Lam, V. W. Y., Allison, E. H., Bell, J. D., Bly he, J., Cheung, W. W. L., F öliche , T. L.,
Gasalla, M. A., & Sumaila, U. R. (2020). Clima e change, opical ishe ies and
p ospec s o sus ainable de elopmen . Na u e Re iews Ea h & En i onmen ,
1(9), 440 454. h ps://doi.o g/10.1038/s43017-020-0071-9
Lance, R. F., & Guan, X. (2020). Va ia ion in inhibi o e ec s on qPCR assays and
implica ions o eDNA su eys. Canadian Jou nal o Fishe ies and Aqua ic
Sciences, 77(1), 23 33. h ps://doi.o g/10.1139/cj as-2018-0263
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
126
Lapoin e, N. W. R., Co kum, L. D., & Mand ak, N. E. (2006). A compa ison o me hods
o sampling ish di e si y in shallow o sho e wa e s o la ge i e s [A icle].
No h Ame ican Jou nal o Fishe ies Managemen , 26(3), 503-513.
h ps://doi.o g/10.1577/m05-091.1
Lassalle, G., Begue , M., Beaula on, L., & Rocha d, E. (2008). Diad omous ish
conse a ion plans need o conside global wa ming issues: An app oach using
biogeog aphical models. Biological Conse a ion, 141(4), 1105-1118.
h ps://doi.o g/10.1016/j.biocon.2008.02.010
Lee, H.-T., Liao, C.-H., & Hsu, T.-H. (2021). En i onmen al DNA (eDNA)
Me aba coding in he Fish Ma ke and Nea by Sea ood Res au an s in Taiwan
Re eals he Unde es ima ion o Fish Species Di e si y in Sea ood. Biology,
10(11), 1132. h ps://doi.o g/10.3390/biology10111132
Lema, S. C., Luckenbach, J. A., Yamamo o, Y., & Housh, M. J. (2024). Fish ep oduc ion
in a wa ming wo ld: ulne able poin s in ho mone egula ion om sex
de e mina ion o spawning. Philosophical T ansac ions o he Royal Socie y B,
379(1898), 20220516. h ps://doi.o g/10.1098/ s b.2022.0516
Lennox, R. J., Pauke , C. P., Aa es up, K., Auge -Mé hé, M., Baumga ne , L., Bi nie-
Gau in, K., Bøe, K., B ink, K., B ownscombe, J. W., Chen, Y., Da idsen, J. G.,
Eliason, E. J., Filous, A., Gillande s, B. M., Helland, I. P., Ho odysky, A. Z.,
Januchowski-Ha ley, S. R., Lowe e-
J. (2019). One Hund ed P essing Ques ions on he Fu u e o Global Fish
Mig a ion Science, Conse a ion, and Policy. F on ie s in Ecology and E olu ion,
7, 286. h ps://doi.o g/10.3389/ e o.2019.00286
Lepage, M., Ha ison, T., B eine, J., Cab al, H., Coa es, S., Gal án, C., Ga cía, P.,
Jage , Z., Kelly, F., Mosch, E. C., Pasquaud, S., Scholle, J., U ia e, A., & Bo ja,
A. (2016). An app oach o in e calib a e ecological classi ica ion ools using ish
in ansi ional wa e o he No h Eas A lan ic. Ecological Indica o s, 67, 318-
327. h ps://doi.o g/10.1016/j.ecolind.2016.02.055
Li, H., Yang, F., Zhang, R., Liu, S., Yang, Z., Lin, L., & Ye, S. (2022). En i onmen al
DNA me aba coding o ish communi ies in a small hyd opowe dam ese oi :
A compa ison be ween he eDNA app oach and es ablished ishing me hods.
REFERENCES
127
Jou nal o F eshwa e Ecology, 37(1), 337 358.
h ps://doi.o g/10.1080/02705060.2022.2086181
Li, J., Lawson Handley, L.-J., Read, D. S., & Hän ling, B. (2018). The e ec o il a ion
me hod on he e iciency o en i onmen al DNA cap u e and quan i ica ion ia
me aba coding. Molecula Ecology Resou ces, 18(5), 1102 1114.
h ps://doi.o g/10.1111/1755-0998.12899
Liang, Z., & Keeley, A. (2013). Fil a ion Reco e y o Ex acellula DNA om
En i onmen al Wa e Samples. En i onmen al Science & Technology, 47(16),
9324 9331. h ps://doi.o g/10.1021/es401342b
Limbu g, K. E., & Waldman, J. R. (2009). D ama ic Declines in No h A lan ic
Diad omous Fishes. BioScience, 59(11), 955-965.
h ps://doi.o g/10.1525/bio.2009.59.11.7
Li le, D. P. (2011). DNA Ba code Sequence Iden i ica ion Inco po a ing Taxonomic
Hie a chy and wi hin Taxon Va iabili y. PLoS One, 6(8), e20552.
h ps://doi.o g/10.1371/jou nal.pone.0020552
Pa hway o Inc ease S anda ds and Compe ency o eDNA Su eys (PISCeS)
Ad ancing collabo a ion and s anda diza ion e o s in he ield o eDNA.
En i onmen al DNA, 2(3), 255 260. h ps://doi.o g/10.1002/edn3.112
Luo, C., Jiang, Z., Wang, C., & Hu, Z. (2015). Rela i e con ibu ion a io: A
quan i a i e me ics o mul i-pa ame e analysis. Cogen Ma hema ics, 2(1),
1068979. h ps://doi.o g/10.1080/23311835.2015.1068979
Mächle , E., Deine , K., Spahn, F., & Al e ma , F. (2016). Fishing in he Wa e : E ec
o Sampled Wa e Volume on En i onmen al DNA-Based De ec ion o
Mac oin e eb a es. En i on Sci Technol, 50(1), 305-312.
h ps://doi.o g/10.1021/acs.es .5b04188
Ma chand, C., Lallie -Ve gès, E., & Bal ze , F. (2003). The composi ion o sedimen a y
o ganic ma e in ela ion o he dynamic ea u es o a mang o e- inged coas in
F ench Guiana. Es ua ine, coas al and shel science, 56(1), 119-130.
h ps://doi.o g/10.1016/S0272-7714(02)00134-8
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
128
Ma iani, S., Baillie, C., Colosimo, G., & Riesgo, A. (2019). Sponges as na u al
en i onmen al DNA sample s. Cu en Biology, 29(11), R401-R402. h ps://doi.
o g/10.1016/j.cub.2019.04.031.
Ma iani, S., Fe nandez, C., Baillie, C., Magalon, H., & Jaqueme , S. (2021). Sha k and
ay di e si y, abundance and empo al a ia ion a ound an Indian Ocean Island,
in e ed by eDNA me aba coding. Conse a ion Science and P ac ice, 3(6), e407.
h ps://doi.o g/10.1111/csp2.407
Ma ques, V., Milhau, T., Albouy, C., Dejean, T., Manel, S., Mouillo , D., & Juhel, J. B.
(2021). GAPeDNA: Assessing and mapping global species gaps in gene ic
da abases o eDNA me aba coding. Di e si y and Dis ibu ions, 27(10), 1880-
1892. h ps://doi.o g/10.1111/ddi.13142
-Be hou, E. (2013). A global
assessmen o eshwa e ish in oduc ions in medi e anean-clima e egions.
Hyd obiologia, 719(1), 317 329. h ps://doi.o g/10.1007/s10750-013-1486-9
Ma in, M. (2011). Cu adap emo es adap e sequences om high- h oughpu
sequencing eads. EMBne . jou nal, 17(1), 10-12.
h ps://doi.o g/10.14806/ej.17.1.200
Ma uyama, A., Nakamu a, K., Yamanaka, H., Kondoh, M., & Minamo o, T. (2015). Da a
om: The elease a e o en i onmen al DNA om ju enile and adul ish
(Ve sion 1, p. 57323 by es) [da ase ]. D yad.
h ps://doi.o g/10.5061/DRYAD.3QB7T
Ma uyama, A., Suga ani, K., Wa anabe, K., Yamanaka, H., & Imamu a, A. (2018).
En i onmen al DNA analysis as a non-in asi e quan i a i e ool o ep oduc i e
mig a ion o a h ea ened endemic ish in i e s. Ecology and E olu ion, 8(23),
11964 11974. h ps://doi.o g/10.1002/ece3.4653
Ma wayana, O. N., Gold, Z., Meye , C. P., & Ba be , P. H. (2022). En i onmen al DNA
in a global biodi e si y ho spo : Lessons om co al ee ish di e si y ac oss he
Indonesian a chipelago. En i onmen al DNA, 4(1), 222 238.
h ps://doi.o g/10.1002/edn3.257
REFERENCES
129
McCa in, L. J., Go inda ajan, A. F., McDe mo , J. M., & He e a, S. (2024).
En i onmen al DNA T anspo a an O sho e Mesopho ic Bank in he
No hwes e n Gul o Mexico. bioRxi , 2024.2008.2026.609783.
h ps://doi.o g/10.1101/2024.08.26.609783
McIn y e, N., He i age, S. N., Lucas, M., G ea es, R., Bubb, D., & Kemp, P. (2007).
COMMISSIONED REPORT.
Meekan, M., Aus in, C. M., Tan, M. H., Wei, N.-W. V., Mille , A., Pie ce, S. J., Rowa ,
D., S e ens, G., Da ies, T. K., & Ponzo, A. (2017). iDNA a sea: Reco e y o
whale sha k (Rhincodon ypus) mi ochond ial DNA sequences om he whale
sha k copepod (Panda us hincodonicus) con i ms global popula ion s uc u e.
F on ie s in Ma ine Science, 4, 420. h ps://doi.o g/10.3389/ ma s.2017.00420
Mille , D. A. W., Wei , L. A., McClin ock, B. T., G an , E. H. C., Bailey, L. L., & Simons,
T. R. (2012). Expe imen al in es iga ion o alse posi i e e o s in audi o y
species occu ence su eys. Ecological Applica ions, 22(5), 1665 1674.
h ps://doi.o g/10.1890/11-2129.1
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
136
Lo elock, C. E. (2017). Using eDNA o de e mine he sou ce o o ganic ca bon
in seag ass meadows. Limnology and Oceanog aphy, 62(3), 1254 1265.
h ps://doi.o g/10.1002/lno.10499
Richa ds, J. L., Sheng, V., Chung, H. W. Y., Liu, M., Tsang, R. H. H., McIl oy, S. E., &
ma ke s. Me hods in Ecology and E olu ion, 13(7), 1568 1580.
h ps://doi.o g/10.1111/2041-210X.13842
Robson, H. L. A., Noble, T. H., Saunde s, R. J., Robson, S. K. A., Bu ows, D. W., &
EDNA echnology
o in asi e ish de ec ion in opical eshwa e ecosys ems. Molecula Ecology
Resou ces, 16(4), 922 932. h ps://doi.o g/10.1111/1755-0998.12505
Rod íguez-Cas o, K. G., Sa anholi, B. H., de Oli ei a, M. E., & Sales, N. G. (2023).
En i onmen al and In e eb a e-De i ed DNA: A Powe ul App oach o
Su eying and Moni o ing Biodi e si y. In Conse a ion Gene ics in he
Neo opics (pp. 453-472). Sp inge . h ps://doi.o g/h ps://doi.o g/10.1007/978-3-
031-34854-9_18
Roussel, A., Beng, K. C., Al e , S. E., Roge , F., Holman, L. E., S ewa , K. A.,
Monaghan, M. T., Mau isseau, Q., Mi imin, L., Wangens een, O. S., An ognazza,
C. M.,
be ween educing complex e minology and p oducing accu a e in e p e a ions
e al., (2020). Molecula Ecology, 30(19), 4601 4605.
h ps://doi.o g/10.1111/mec.15942
Rod íguez-Ezpele a, N., Zinge , L., Kinzige , A., Bik, H. M., Bonin, A., Coissac, E.,
Eme son, B. C., Lopes, C. M., Pelle ie , T. A., Tabe le , P., & Na um, S. (2021).
REFERENCES
137
Biodi e si y moni o ing using en i onmen al DNA.
h ps://doi.o g/doi:10.1111/1755-0998.13399
Eme son, B. C., Lopes, C. M., Pelle ie , T. A., Tabe le , P., & Na um, S. (2021).
Biodi e si y moni o ing using en i onmen al DNA. Molecula Ecology
Resou ces, 21(5), 1405 1409. h ps://doi.o g/10.1111/1755-0998.13399
Rose, G. A. (1993). Cod spawning on a mig a ion highway in he no h-wes A lan ic.
Na u e, 366(6454), 458 461. h ps://doi.o g/10.1038/366458a0
Rou ke, M. L., Fowle , A. M., Hughes, J. M., B oadhu s , M. K., DiBa is a, J. D., Fielde ,
S., Wilkes Walbu n, J., & Fu lan, E. M. (2022). En i onmen al DNA (eDNA) as
a ool o assessing ish biomass: A e iew o app oaches and u u e
conside a ions o esou ce su eys. En i onmen al DNA, 4(1), 9 33.
h ps://doi.o g/10.1002/edn3.185
Ruan, H.-T., Wang, R.-L., Li, H.-T., Liu, L., Kuang, T.-X., Li, M., & Zou, K.-S. (2022).
E ec s o sampling s a egies and DNA ex ac ion me hods on eDNA
me aba coding: A case s udy o es ua ine ish di e si y moni o ing. Zoological
Resea ch, 43(2), 192 204. h ps://doi.o g/10.24272/j.issn.2095-8137.2021.331
Ruppe , K. M., Kline, R. J., & Rahman, M. S. (2019). Pas , p esen , and u u e
pe spec i es o en i onmen al DNA (eDNA) me aba coding: A sys ema ic e iew
in me hods, moni o ing, and applica ions o global eDNA. Global Ecology and
Conse a ion, 17, e00547. h ps://doi.o g/10.1016/j.gecco.2019.e00547
Saeed, M., Rais, M., Ak am, A., Williams, M. R., Kellne , K. F., Hashsham, S. A., &
Da is, D. R. (2022). De elopmen and alida ion o an eDNA p o ocol o
moni o ing endemic Asian spiny ogs in he Himalayan egion o Pakis an.
Scien i ic Repo s, 12(1), 5624. h ps://doi.o g/10.1038/s41598-022-09084-1
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
138
Sahoo, P. K., Mohan y, J., Ga nayak, S., Mohan y, B., Ka , B., P asan h, H., & Jena, J.
(2013). Es ima ion o loss due o a gulosis in ca p cul u e ponds in India. Indian
J Fish, 60(2), 99-102.
Sain ilan, N., Roge s, K., Mazumde , D., & Wood o e, C. (2013). Alloch honous and
au och honous con ibu ions o ca bon accumula ion and ca bon s o e in
sou heas e n Aus alian coas al we lands. Es ua ine, coas al and shel science,
128, 84-92. h ps://doi.o g/10.1016/j.ecss.2013.05.010
Sa ka , U. K., Roy, K., Ka na ak, G., Naska , M., Pu hiyo il, M., Baksi, S.,
Lian huamluaia, L., Kuma i, S., Ghosh, B. D., & Das, B. K. (2021). Rep oduc i e
en i onmen o he dec easing Indian i e shad in Asian inland wa e s:
Disen angling he clima e change and indisc imina i e ishing h ea s.
En i onmen al Science and Pollu ion Resea ch, 28, 30207 30218.
Sa hianandan, T. V., Mohamed, K. S., Jayasanka , J., Ku iakose, S., Mini, K. G.,
Va ghese, E., Zacha ia, P. U., Kaladha an, P., Najmudeen, T. M., Koya, M. K.,
Sasikuma , G., Bha i, V., Rohi , P., Maheswa udu, G., Sindhu, K. A., S eep iya,
V., Alphonsa, J., & Deep hi, A. (2021). S a us o Indian ma ine ish s ocks:
Modelling s ock biomass dynamics in mul igea ishe ies. ICES Jou nal o
Ma ine Science, 78(5), 1744 1757. h ps://doi.o g/10.1093/icesjms/ sab076
Saunde s, M. D., S ee es, R., MacIn y e, L. P., Knysh, K. M., Co in, M. R. S.,
Boud eau, M., Pa e , C. C., Heu el, M. R. . d., & Cou enay, S. C. (2024).
Moni o ing es ua ine ish communi ies: en i onmen al DNA (eDNA)
me aba coding as a complemen o beach seining. Canadian Jou nal o
Fishe ies and Aqua ic Sciences, 0(0), null. h ps://doi.o g/10.1139/cj as-2023-
0227
Schloesse , N. (2018). Co ela ing sea lamp ey densi y wi h en i onmen al DNA
de ec ions in he lab. Managemen o Biological In asions, 9(4), 483-495.
h ps://doi.o g/10.3391/mbi.2018.9.4.11
Schloss, P. D., Wes co , S. L., Ryabin, T., Hall, J. R., Ha mann, M., Hollis e , E. B.,
Lesniewski, R. A., Oakley, B. B., Pa ks, D. H., Robinson, C. J., Sahl, J. W.,
S es, B., Thallinge , G. G., Van Ho n, D. J., & Webe , C. F. (2009). In oducing
mo hu : Open-Sou ce, Pla o m-Independen , Communi y-Suppo ed So wa e
REFERENCES
139
o Desc ibing and Compa ing Mic obial Communi ies. Appl En i on
Mic obiol, 75(23), 7537-7541. h ps://doi.o g/10.1128/aem.01541-09
Laakmann, S., & Sal ons all, K. (2023). En i onmen al DNA (eDNA) e eals
po en ial o in e oceanic ish in asions ac oss he Panama Canal. Ecol E ol,
13(1), e9675. h ps://doi.o g/10.1002/ece3.9675
Schus e , C. J., Mu ay, K. N., Sande s, J. L., & Ken , M. L. (2023). Applica ion o an
eDNA assay o he de ec ion o Pseudoloma neu ophilia (Mic ospo idia) in
zeb a ish (Danio e io) acili ies. Aquacul u e, 564, 739044.
h ps://doi.o g/10.1016/j.aquacul u e.2022.739044
Shea, D., Ba eman, A., Li, S., Taba a, A., Schulze, A., Mo decai, G., Ogs on, L., Volpe,
En i onmen al DNA om mul iple pa hogens is ele a ed nea ac i e A lan ic
salmon a ms. P oceedings o he Royal Socie y B: Biological Sciences,
287(1937), 20202010. h ps://doi.o g/10.1098/ spb.2020.2010
Siemes, R. W. A., Duong, T. M., Bo sje, B. W., & Hulsche , S. J. M. H. (2024).
Clima e Change Can In ensi y he E ec s o Local In e en ions: A
Mo phological Modeling S udy o a Highly Enginee ed Es ua y. Jou nal o
Geophysical Resea ch: Ea h Su ace, 129(7).
h ps://doi.o g/10.1029/2023j 007595
Sigsgaa d, E. E., Ca l, H., Mølle , P. R., & Thomsen, P. F. (2015). Moni o ing he nea -
ex inc Eu opean wea he loach in Denma k based on en i onmen al DNA om
wa e samples. Biological Conse a ion, 183, 46 52.
h ps://doi.o g/10.1016/j.biocon.2014.11.023
Sigsgaa d, E. E., Nielsen, I. B., Bach, S. S., Lo enzen, E. D., Robinson, D. P., Knudsen,
S. W., Pede sen, M. W., Jaidah, M. A., O lando, L., Wille sle , E., Mølle , P. R.,
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
140
& Thomsen, P. F. (2017). Popula ion cha ac e is ics o a la ge whale sha k
agg ega ion in e ed om seawa e en i onmen al DNA. Na u e Ecology &
E olu ion, 1(1), 0004. h ps://doi.o g/10.1038/s41559-016-0004
Sil a, S., Ba ca, S., Viei a-Lane o, R., & Cobo, F. (2019). Ups eam mig a ion o he
anad omous sea lamp ey (<i>Pe omyzon ma inus</i> Linnaeus, 1758) in a highly
impounded i e : Impac o low-head obs acles and ishe ies [A icle]. Aqua ic
Conse a ion-Ma ine and F eshwa e Ecosys ems, 29(3), 389-396.
h ps://doi.o g/10.1002/aqc.3059
Sil a, S., Se ia, M. J., Viei a-Lane o, R., & Cobo, F. (2013). Downs eam mig a ion
and hema ophagous eeding o newly me amo phosed sea lamp eys
(<i>Pe omyzon ma inus</i> Linnaeus, 1758) [A icle]. Hyd obiologia, 700(1),
277-286. h ps://doi.o g/10.1007/s10750-012-1237-3
Skel on, J., Cau in, A., & Hun e , M. (2023). En i onmen al DNA me aba coding ead
numbe s and hei a iabili y p edic species abundance, bu weakly in non-
dominan species. En i onmen al DNA, 5(5), 1092-1104.
h ps://doi.o g/10.1002/edn3.355
Sma , J., Gill, J. A., Su he land, W. J., & Wa kinson, A. R. (2006). G assland-b eeding
wade s: Iden i ying key habi a equi emen s o managemen . Jou nal o Applied
Ecology, 43(3), 454 463. h ps://doi.o g/10.1111/j.1365-2664.2006.01166.x
Smi h, S. N., Schlupp, I., Higgins, E. D., Wa e s, J. L., Benne , K., B äge , S., & Sile ,
C. D. (2022). De elopmen and alida ion o an en i onmen al DNA p o ocol o
de ec an in asi e Ca ibbean eshwa e ish, he guppy ( Poecilia e icula a ).
En i onmen al DNA, 4(2), 304 310. h ps://doi.o g/10.1002/edn3.248
Sokolo a, M., & Lapalme, G. (2009). A sys ema ic analysis o pe o mance measu es
o classi ica ion asks. In o ma ion P ocessing & Managemen , 45(4), 427-437.
h ps://doi.o g/10.1016/j.ipm.2009.03.002
Souza, G. B. G., & Vianna, M. (2020). Fish-based indices o assessing ecological
quali y and bio ic in eg i y in ansi ional wa e s: A sys ema ic e iew.
REFERENCES
141
Ecological Indica o s, 109, 105665.
h ps://doi.o g/10.1016/j.ecolind.2019.105665
Spea , M. J., Embke, H. S., K ysan, P. J., & Vande Zanden, M. J. (2021). Applica ion o
eDNA as a ool o assessing ish popula ion abundance. En i onmen al DNA,
3(1), 83 91. h ps://doi.o g/10.1002/edn3.94
Spea , S. F., G o es, J. D., Williams, L. A., & Wai s, L. P. (2015). Using en i onmen al
DNA me hods o imp o e de ec abili y in a hellbende (C yp ob anchus
alleganiensis) moni o ing p og am. Biological Conse a ion, 183, 38 45.
h ps://doi.o g/10.1016/j.biocon.2014.11.016
Spens, J., E ans, A. R., Hal mae en, D., Knudsen, S. W., Sengup a, M. E., Mak, S. S.
T., Sigsgaa d, E. E., & Hells öm, M. (2017). Compa ison o cap u e and s o age
me hods o aqueous mac obial eDNA using an op imized ex ac ion p o ocol:
ad an age o enclosed il e . Me hods in Ecology and E olu ion, 8(5), 635-645.
S iHa i, M., Pa an-Kuma , A., K ishnan, P., Ram eke, K., Ayya hu ai, K., S eekan h, G.,
& kuma Jaiswa , A. (2022). Me a-analysis o ish s ock iden i ica ion in India:
cu en s a us and u u e pe spec i es. Ma ine and F eshwa e Resea ch, 74(2),
99-110. h p://dx.doi.o g/10.1071/MF22151
S a , M., Hugge , M. J., Be nasconi, R., DiBa is a, J. D., Be y, T. E., Newman, S. J.,
Ha ey, E. S., & Bunce, M. (2017). Ecosys em biomoni o ing wi h eDNA:
Me aba coding ac oss he ee o li e in a opical ma ine en i onmen . Scien i ic
Repo s, 7(1), 12240. h ps://doi.o g/10.1038/s41598-017-12501-5
S en i o d, G., Ba eman, I., Hinchli e, S., Bass, D., Ha nell, R., San os, E., De lin, M.,
Feis , S., Taylo , N., & Ve ne -Je eys, D. (2020). Sus ainable aquacul u e
h ough he One Heal h lens. Na u e Food, 1(8), 468-474.
h ps://doi.o g/10.1038/s43016-020-0127-5
S oeckle, M. Y., Das Mishu, M., & Cha lop-Powe s, Z. (2020). Imp o ed En i onmen al
DNA Re e ence Lib a y De ec s O e looked Ma ine Fishes in New Je sey, Uni ed
S a es. F on ie s in Ma ine Science, 7, 226.
h ps://doi.o g/10.3389/ ma s.2020.00226
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
142
S oeckle, M. Y., Sobole a, L., & Cha lop-Powe s, Z. (2017). Aqua ic en i onmen al
DNA de ec s seasonal ish abundance and habi a p e e ence in an u ban es ua y.
PLOS ONE, 12(4), e0175186. h ps://doi.o g/10.1371/jou nal.pone.0175186
S o beck, F., & Daan, B. (2001). Fish species ecogni ion using compu e ision and a
neu al ne wo k. Fishe ies Resea ch, 51(1), 11 15. h ps://doi.o g/10.1016/S0165-
7836(00)00254-X
S ibling, J. B., Pa lik, K. L., Holdswo h, S. M., & Leppo, E. W. (2008). Da a quali y,
pe o mance, and unce ain y in axonomic iden i ica ion o biological
assessmen s. Jou nal o he No h Ame ican Ben hological Socie y, 27(4), 906-
919. h ps://doi.o g/10.1899/07-175.1
S ickle , K. M., F emie , A. K., & Goldbe g, C. S. (2015). Quan i ying e ec s o UV-B,
empe a u e, and pH on eDNA deg ada ion in aqua ic mic ocosms. Biological
Conse a ion, 183, 85 92. h ps://doi.o g/10.1016/j.biocon.2014.11.038
Tabe le , P., Coissac, E., Hajibabaei, M., & Riesebe g, L. H. (2012). En i onmen al
DNA. Molecula Ecology, 21(8), 1789 1793. h ps://doi.o g/10.1111/j.1365-
294X.2012.05542.x
Taengphu, S., Kayansam uaj, P., Kawa o, Y., Delama e-Debou e ille, J., Mohan, C. V.,
Dong, H. T., & Senapin, S. (2022). Concen a ion and quan i ica ion o Tilapia
ilapine i us om wa e using a simple i on loccula ion coupled wi h p obe-
based RT-qPCR. Pee J, 10, e13157.
Takaha a, T., Iwai, N., Yasumiba, K., & Igawa, T. (2020). Compa ison o he de ec ion
o 3 endange ed og species by eDNA and acous ic su eys ac oss 3 seasons.
F eshwa e Science, 39(1), 18-27. h ps://doi.o g/10.1086/707365
Takaha a, T., Minamo o, T., Yamanaka, H., Doi, H., & Kawaba a, Z. (2012). Es ima ion
o Fish Biomass Using En i onmen al DNA. PLoS ONE, 7(4), e35868.
h ps://doi.o g/10.1371/jou nal.pone.0035868
REFERENCES
143
Takeuchi, A., Iijima, T., Kakuzen, W., Wa anabe, S., Yamada, Y., Okamu a, A., Ho ie,
N., Mikawa, N., Mille , M. J., Kojima, T., & Tsukamo o, K. (2019). Release o
eDNA by di e en li e his o y s ages and du ing spawning ac i i ies o
labo a o y- ea ed Japanese eels o in e p e a ion o oceanic su ey da a.
Scien i ic Repo s, 9(1), 6074. h ps://doi.o g/10.1038/s41598-019-42641-9
Tama io, C., Sunde, J., Pe e sson, E., Tibblin, P., & Fo sman, A. (2019). Ecological and
E olu iona y Consequences o En i onmen al Change and Managemen Ac ions
o Mig a ing Fish. F on ie s in Ecology and E olu ion, 7.
h ps://doi.o g/10.3389/ e o.2019.00271
Tama io, C., Sunde, J., Pe e sson, E., Tibblin, P., & Fo sman, A. (2019). Ecological and
E olu iona y Consequences o En i onmen al Change and Managemen Ac ions
o Mig a ing Fish. F on ie s in Ecology and E olu ion, 7, 271.
h ps://doi.o g/10.3389/ e o.2019.00271
Ta e ny, C., & Elie, P. (2009). Bilan des connaissances biologiques e de l'é a des
habi a s des lamp oies mig a ices dans le bassin de la Gi onde: p oposi ions
d'ac ions p io i ai es.
Tes a, J. M., Kemp, W. M., Ha is, L. A., Woodland, R. J., & Boyn on, W. R. (2017).
Challenges and Di ec ions o he Ad ancemen o Es ua ine Ecosys em
Science. Ecosys ems, 20(1), 14-22. h ps://doi.o g/10.1007/s10021-016-0004-0
Thalinge , B., Wol , E., T augo , M., & Wanzenböck, J. (2019). Moni o ing spawning
mig a ions o po amod omous ish species ia eDNA. Scien i ic Repo s, 9(1),
15388. h ps://doi.o g/10.1038/s41598-019-51398-0
Thomas, A. C., Tank, S., Nguyen, P. L., Ponce, J., Sinnesael, M., & Goldbe g, C. S.
(2020). A sys em o apid eDNA de ec ion o aqua ic in asi e species.
En i onmen al DNA, 2(3), 261 270. h ps://doi.o g/10.1002/edn3.25
Thomsen, P. F., & Sigsgaa d, E. E. (2019). En i onmen al DNA me aba coding o wild
lowe s e eals di e se communi ies o e es ial a h opods. Ecology and
E olu ion, 9(4), 1665 1679. h ps://doi.o g/10.1002/ece3.4809
Thomsen, P. F., & Wille sle , E. (2015). En i onmen al DNA An eme ging ool in
conse a ion o moni o ing pas and p esen biodi e si y. Biological
Conse a ion, 183, 4 18. h ps://doi.o g/10.1016/j.biocon.2014.11.019
Ad ancing en i onmen al DNA app oaches o op imizing aqua ic ecosys em moni o ing and ecological assessmen
144
Thomsen, P. F., Jensen, M. R., & Sigsgaa d, E. E. (2024). A ision o global eDNA-
based moni o ing in a changing wo ld. Cell.
h ps://doi.o g/10.1016/j.cell.2024.04.019
Thomsen, P. F., Kielgas , J., I e sen, L. L., Mølle , P. R., Rasmussen, M., & Wille sle ,
E. (2012). De ec ion o a Di e se Ma ine Fish Fauna Using En i onmen al DNA
om Seawa e Samples. PLoS ONE, 7(8), e41732.
h ps://doi.o g/10.1371/jou nal.pone.0041732
Thomsen, P. F., Kielgas , J., I e sen, L. L., Wiu , C., Rasmussen, M., Gilbe , M. T. P.,
O lando, L., & Wille sle , E. (2012). Moni o ing endange ed eshwa e
biodi e si y using en i onmen al DNA: SPECIES MONITORING BY
ENVIRONMENTAL DNA. Molecula Ecology, 21(11), 2565 2573.
h ps://doi.o g/10.1111/j.1365-294X.2011.05418.x
Tillo son, M. D., Kelly, R. P., Duda, J. J., Hoy, M., K alj, J., & Quinn, T. P. (2018).
Concen a ions o en i onmen al DNA (eDNA) e lec spawning salmon
abundance a ine spa ial and empo al scales. Biological Conse a ion, 220, 1
11. h ps://doi.o g/10.1016/j.biocon.2018.01.030
Tkachuk, K. A., & Dunn, D. A. (2020). Analysis o sea lamp ey en i onmen al DNA
du ing lamp icide ea men in a ibu a y o Lake On a io. Knowledge &
Managemen o Aqua ic Ecosys ems(421), 14.
h ps://doi.o g/10.1051/kmae/2020006
REFERENCES
145
T ebi z, A. S., Ho man, J. C., Da ling, J. A., Pilg im, E. M., Kelly, J. R., B own, E. A.,
Chadde on, W. L., Egan, S. P., G ey, E. K., Hashsham, S. A., Klymus, K. E.,
Mahon, A. R., Ram, J. L., Schul z, M. T., S epien, C. A., & Scha d , J. C. (2017).
Ea ly de ec ion moni o ing o aqua ic non-indigenous species: Op imizing
su eillance, inco po a ing ad anced echnologies, and iden i ying esea ch
needs. Jou nal o En i onmen al Managemen , 202, 299 310.
h ps://doi.o g/10.1016/j.jen man.2017.07.045
T éguie , A., Paillisson, J.-M., Dejean, T., Valen ini, A., Schlaep e , M. A., & Roussel,
J.-M. (2014). En i onmen al DNA su eillance o in e eb a e species:
Ad an ages and echnical limi a ions o de ec in asi e c ay ish P ocamba us
cla kii in eshwa e ponds. Jou nal o Applied Ecology, 51(4), 871 879.
h ps://doi.o g/10.1111/1365-2664.12262
T ujillo-González, A., Edmunds, R., Becke , J., & Hu son, K. (2019). Pa asi e de ec ion
in he o namen al ish ade using en i onmen al DNA. Sci Rep, 9(1), 5173.
h ps://www.na u e.com/a icles/s41598-019-41517-2
Tsukamo o, K. (2006). Spawning o eels nea a seamoun . Na u e, 439(7079), 929 929.
h ps://doi.o g/10.1038/439929a
Tu on, M., Angulo-P eckle , C., An ich, A., P æbel, K., & Wangens een, O. S. (2020).
Mo e han expec ed om old sponge samples: A na u al sample DNA
me aba coding assessmen o ma ine ish di e si y in Nha T ang Bay (Vie nam).
F on ie s in Ma ine Science, 7, 605148.
h ps://doi.o g/10.3389/ ma s.2020.605148
UICN Comi é ançais, M., SFI & AFB. (2019). La Lis e ouge des espèces menacées en
F ance
