Mission Blue Voyage
Daniel Pauly: The ocean's shifting baseline
Dnijel Poli (Daniel Pauly): Pomeranje nivoa okeanskog dna
Filmed:
Readability: 3.8
254,411 views
Okeani su se promenili tokom naših života, a to je prikazano kroz smanjenje prosečnih veličina riba. Danijel Poli nam u ovom govoru, održanom u Mission Blue, pokazuje da svaki put kada se promeni nivo dna mora, zovemo to novim "normalnim" stanjem. Kada ćemo to prestati da radimo?
Daniel Pauly - Fisheries biologist
Daniel Pauly is the principal investigator at the Sea Around Us Project, which studies the impact of the world's fisheries on marine ecosystems. The software he's helped develop is used around the world to model and track the ocean. Full bio
Daniel Pauly is the principal investigator at the Sea Around Us Project, which studies the impact of the world's fisheries on marine ecosystems. The software he's helped develop is used around the world to model and track the ocean. Full bio
Double-click the English transcript below to play the video.
00:12
I'm going to speak
0
0
2000
Govoriću
00:14
about a tiny, little idea.
1
2000
3000
o jednoj maloj ideji.
00:17
And this is about shifting baseline.
2
5000
4000
A to je pomeranje dna mora.
00:21
And because the idea can be explained in one minute,
3
9000
4000
Pošto ovo može da se objasni u roku od jedne minute,
00:25
I will tell you three stories before
4
13000
3000
ispričaću vam 3 priče
00:28
to fill in the time.
5
16000
2000
da bih ispunio vreme.
00:30
And the first story
6
18000
2000
Prva priča
00:32
is about Charles Darwin, one of my heroes.
7
20000
3000
je o Čarlsu Darvinu, jednom od mojih heroja.
00:35
And he was here, as you well know, in '35.
8
23000
3000
On je boravio ovde, 1835.
00:38
And you'd think he was chasing finches,
9
26000
2000
Pomislili biste da je došao da juri zebe,
00:40
but he wasn't.
10
28000
2000
ali zapravo nije.
00:42
He was actually collecting fish.
11
30000
2000
On je ovde sakupljao ribe.
00:44
And he described one of them
12
32000
2000
Jednu od njih je opisao
00:46
as very "common."
13
34000
2000
kao veoma učestalu vrstu.
00:48
This was the sailfin grouper.
14
36000
2000
Ta riba je škarpina zrakoperka.
00:50
A big fishery was run on it
15
38000
2000
Mnogi su lovili ovde zbog ove ribe
00:52
until the '80s.
16
40000
3000
sve do osamdesetih.
00:55
Now the fish is on the IUCN Red List.
17
43000
3000
Ova riba se nalazi na Crvenoj listi
Međunarodne unije za očuvanje prirode.
Međunarodne unije za očuvanje prirode.
00:58
Now this story,
18
46000
2000
Ovu priču
01:00
we have heard it lots of times
19
48000
3000
smo čuli toliko puta
01:03
on Galapagos and other places,
20
51000
2000
na Galapagosu i na drugim mestima
01:05
so there is nothing particular about it.
21
53000
3000
i ona nije ništa posebno.
01:08
But the point is, we still come to Galapagos.
22
56000
3000
Ali u ovom trenutku, mi i dalje posećujemo Galapagos.
01:11
We still think it is pristine.
23
59000
3000
Još uvek smatramo da je to drevno mesto.
01:14
The brochures still say
24
62000
3000
I dan danas u brošurama piše
01:17
it is untouched.
25
65000
2000
da je tu potpuno netaknuta priroda.
01:19
So what happens here?
26
67000
3000
Dakle, šta se ovde dešava?
01:22
The second story, also to illustrate another concept,
27
70000
3000
Druga priča, koja opisuje jedan drugi koncept,
01:25
is called shifting waistline.
28
73000
2000
zove se pomeranje obima struka.
01:27
(Laughter)
29
75000
3000
(Smeh)
01:30
Because I was there in '71,
30
78000
2000
Pošto sam tamo bio 1971. godine
01:32
studying a lagoon in West Africa.
31
80000
2000
proučavajući lagune u zapadnoj Africi.
01:34
I was there because I grew up in Europe
32
82000
3000
Bio sam tamo jer sam odrastao u Evropi
01:37
and I wanted later to work in Africa.
33
85000
2000
i želeo sam da kasnije radim u Africi.
01:39
And I thought I could blend in.
34
87000
2000
Pomislio sam da bih mogao da se uklopim.
01:41
And I got a big sunburn,
35
89000
2000
Prilično sam izgoreo na suncu
01:43
and I was convinced that I was really not from there.
36
91000
3000
i bio sam sasvim uveren da ne pripadam tamo.
01:46
This was my first sunburn.
37
94000
2000
Prvi put sam tada izgoreo na suncu.
01:48
And the lagoon
38
96000
3000
Laguna
01:51
was surrounded by palm trees,
39
99000
2000
je bila okružena palmama,
01:53
as you can see, and a few mangrove.
40
101000
2000
kao što vidite ovde i sa nekoliko mangrova.
01:55
And it had tilapia
41
103000
2000
Bilo je tu i tilapija
01:57
about 20 centimeters,
42
105000
2000
dužine 20 centimetara,
01:59
a species of tilapia called blackchin tilapia.
43
107000
2000
vrsta tilapije koja se zove crnobrada tilapija.
02:01
And the fisheries for this tilapia
44
109000
2000
Lovišta za ovu vrstu tilapije
02:03
sustained lots of fish and they had a good time
45
111000
3000
su držala veliki broj riba
02:06
and they earned more than average
46
114000
2000
i zarađivala su više od proseka
02:08
in Ghana.
47
116000
2000
u Gani.
02:10
When I went there 27 years later,
48
118000
3000
Kada sam se vratio tamo posle 27 godina,
02:13
the fish had shrunk to half of their size.
49
121000
3000
ribe su se znatno smanjile, gotovo prepolovile.
02:16
They were maturing at five centimeters.
50
124000
2000
Sazrevale su sa svega 5 centimetara.
02:18
They had been pushed genetically.
51
126000
2000
Genetski su bile modifikovane.
02:20
There were still fishes.
52
128000
2000
Još je bilo ribe
02:22
They were still kind of happy.
53
130000
2000
i svi su bili zadovoljni.
02:24
And the fish also were happy to be there.
54
132000
5000
I ribe su bile zadovoljne što su tamo.
02:29
So nothing has changed,
55
137000
2000
Dakle, ništa se nije promenilo,
02:31
but everything has changed.
56
139000
2000
ali se sve promenilo.
02:33
My third little story
57
141000
2000
Moja treća priča
02:35
is that I was an accomplice
58
143000
2000
je to da sam bio saučesnik
02:37
in the introduction of trawling
59
145000
2000
u uvođenju mrežnog ribarenja
02:39
in Southeast Asia.
60
147000
2000
u jugoistočnoj Aziji.
02:41
In the '70s -- well, beginning in the '60s --
61
149000
3000
Sedamdesetih, zapravo početkom šezdesetih,
02:44
Europe did lots of development projects.
62
152000
3000
Evropa je učestvovala u mnogim razvojnim projektima.
02:47
Fish development
63
155000
2000
Razvoj ribarstva
02:49
meant imposing on countries
64
157000
2000
je značio nametanje državama,
02:51
that had already 100,000 fishers
65
159000
3000
koje su već imale oko 100 hiljada ribara,
02:54
to impose on them industrial fishing.
66
162000
3000
da uvedu industrijski vid ribarenja.
02:57
And this boat, quite ugly,
67
165000
2000
Ovaj brod, prilično ružan,
02:59
is called the Mutiara 4.
68
167000
2000
se zove Mutijara 4.
03:01
And I went sailing on it,
69
169000
2000
Plovio sam na njemu,
03:03
and we did surveys
70
171000
3000
radio istraživanje, ankete
03:06
throughout the southern South China sea
71
174000
3000
kroz oblasti Južnog kineskog mora,
03:09
and especially the Java Sea.
72
177000
2000
posebno na Javanskom moru.
03:11
And what we caught,
73
179000
2000
Ono što smo uhvatili,
03:13
we didn't have words for it.
74
181000
2000
ostali smo bez reči.
03:15
What we caught, I know now,
75
183000
3000
Ono što smo uhvatili je bilo, sada znam,
03:18
is the bottom of the sea.
76
186000
2000
dno mora.
03:20
And 90 percent of our catch
77
188000
2000
90% našeg ulova
03:22
were sponges,
78
190000
2000
su bili sunđeri
03:24
other animals that are fixed on the bottom.
79
192000
3000
i druge životinje koje se nalaze na dnu.
03:27
And actually most of the fish,
80
195000
2000
A zapravo većina ribe
03:29
they are a little spot on the debris,
81
197000
2000
je bila retka pojava na smeću
03:31
the piles of debris, were coral reef fish.
82
199000
3000
i to su bile ribe koralnog grebena.
03:34
Essentially the bottom of the sea came onto the deck
83
202000
2000
Dno mora je bilo na našoj palubi
03:36
and then was thrown down.
84
204000
2000
koju smo potom vraćali nazad.
03:38
And these pictures are extraordinary
85
206000
3000
Ove slike su sjajne
03:41
because this transition is very rapid.
86
209000
3000
jer ova promena je zaista brza.
03:44
Within a year, you do a survey
87
212000
3000
Za samo godinu dana, radite istraživanje
03:47
and then commercial fishing begins.
88
215000
2000
i potom počinje komercijalno ribarenje.
03:49
The bottom is transformed
89
217000
2000
Dno je potpuno promenjeno,
03:51
from, in this case, a hard bottom or soft coral
90
219000
3000
prešlo je od tvrdog ili mekog koralnog dna
03:54
into a muddy mess.
91
222000
3000
u muljeviti haos.
03:57
This is a dead turtle.
92
225000
2000
Ovo je mrtva kornjača.
03:59
They were not eaten, they were thrown away because they were dead.
93
227000
3000
Njih nismo jeli, nego smo ih
bacali nazad jer su bile mrtve.
bacali nazad jer su bile mrtve.
04:02
And one time we caught a live one.
94
230000
2000
Jednom smo upecali i jednu živu.
04:04
It was not drowned yet.
95
232000
2000
Ona se još nije udavila.
04:06
And then they wanted to kill it because it was good to eat.
96
234000
3000
A onda su hteli da je ubiju jer su kornjače ukusne.
04:09
This mountain of debris
97
237000
3000
Ovakve gomile smeća
04:12
is actually collected by fishers
98
240000
3000
sakupe ribari
04:15
every time they go
99
243000
2000
svaki put kada
04:17
into an area that's never been fished.
100
245000
2000
se otisnu na more u kojem nikada nisu lovili.
04:19
But it's not documented.
101
247000
2000
Ali ovo nikada nije dokumentovano.
04:21
We transform the world,
102
249000
2000
Mi smo promenili svet,
04:23
but we don't remember it.
103
251000
2000
ali ne uviđamo to.
04:25
We adjust our baseline
104
253000
3000
Pomeramo našu baznu liniju
04:28
to the new level,
105
256000
2000
na novi nivo
04:30
and we don't recall what was there.
106
258000
4000
i ne sećamo šta je bilo tamo.
04:34
If you generalize this,
107
262000
2000
Ako ovo uopštavate,
04:36
something like this happens.
108
264000
2000
onda se nešto ovako dogodi.
04:38
You have on the y axis some good thing:
109
266000
3000
Na Y osi su dobre stvari:
04:41
biodiversity, numbers of orca,
110
269000
3000
biološka raznolikost, broj orki,
04:44
the greenness of your country, the water supply.
111
272000
3000
zelenilo, zalihe vode.
04:47
And over time it changes --
112
275000
2000
Tokom vremena, to se menja --
04:49
it changes
113
277000
2000
to se menja
04:51
because people do things, or naturally.
114
279000
2000
jer ljudi rade neke stvari ili se menja prirodno.
04:53
Every generation
115
281000
2000
Svaka generacija
04:55
will use the images
116
283000
2000
će koristiti vizije
04:57
that they got at the beginning of their conscious lives
117
285000
3000
koje su dobili na početku svog svesnog života
05:00
as a standard
118
288000
2000
i koristiće to kao standard
05:02
and will extrapolate forward.
119
290000
2000
vrednujući ga kao početak.
05:04
And the difference then,
120
292000
2000
Razlika koju vide
05:06
they perceive as a loss.
121
294000
2000
se procenjuje kao gubitak.
05:08
But they don't perceive what happened before as a loss.
122
296000
3000
Ali ne uviđaju da se pre toga dogodio gubitak.
05:11
You can have a succession of changes.
123
299000
2000
Postoje etape promene.
05:13
At the end you want to sustain
124
301000
3000
Na kraju, ono što želite da održite
05:16
miserable leftovers.
125
304000
3000
su samo jadni ostaci.
05:19
And that, to a large extent, is what we want to do now.
126
307000
3000
To je ono što mi činimo danas.
05:22
We want to sustain things that are gone
127
310000
3000
Želimo da održimo stvari koje su nestale
05:25
or things that are not the way they were.
128
313000
4000
ili koje nisu više onakve kakve su bile.
05:29
Now one should think
129
317000
2000
Neko će pomisliti
05:31
this problem affected people
130
319000
2000
da je ovo uticalo na ljude
05:33
certainly when in predatory societies,
131
321000
4000
u predatorskim društvima,
05:37
they killed animals
132
325000
2000
kada su ubijali životinje,
05:39
and they didn't know they had done so
133
327000
2000
ali nisu uviđali da to rade
05:41
after a few generations.
134
329000
2000
i nakon nekoliko generacija.
05:43
Because, obviously,
135
331000
3000
Jer očigledno,
05:46
an animal that is very abundant,
136
334000
5000
životinje kojih ima na pretek,
05:51
before it gets extinct,
137
339000
3000
pre nego što izumru,
05:54
it becomes rare.
138
342000
3000
postanu jako retke.
05:57
So you don't lose abundant animals.
139
345000
3000
Dakle, ne gubimo životinje kojih ima u izobilju.
06:00
You always lose rare animals.
140
348000
2000
Uvek gubimo retke životinje.
06:02
And therefore they're not perceived
141
350000
2000
Zbog toga to ne smatramo
06:04
as a big loss.
142
352000
2000
velikim gubitkom.
06:06
Over time,
143
354000
2000
Tokom vremena
06:08
we concentrate on large animals,
144
356000
2000
koncentrišemo se na velike životinje,
06:10
and in a sea that means the big fish.
145
358000
2000
u moru su to velike ribe.
06:12
They become rarer because we fish them.
146
360000
3000
One postanu retke jer ih mi pecamo.
06:15
Over time we have a few fish left
147
363000
2000
Tokom vremena sve je manje riba
06:17
and we think this is the baseline.
148
365000
3000
i pomislimo da je to bazna linija.
06:20
And the question is,
149
368000
2000
Pitanje je
06:22
why do people accept this?
150
370000
5000
zbog čega ljudi prihvataju ovo?
06:27
Well because they don't know that it was different.
151
375000
3000
Zato što ne znaju da je ranije bilo drugačije.
06:30
And in fact, lots of people, scientists,
152
378000
3000
Zapravo, mnogi ljudi od kojih su neki i naučnici,
06:33
will contest that it was really different.
153
381000
2000
osporavaće da je stvarno bilo drugačije.
06:35
And they will contest this
154
383000
2000
Oni će osporavati ovo
06:37
because the evidence
155
385000
2000
smatrajući da dokazi
06:39
presented in an earlier mode
156
387000
5000
koji su predstavljeni prema ranijem stanju,
06:44
is not in the way
157
392000
3000
nisu predstavljeni
06:47
they would like the evidence presented.
158
395000
2000
na način na koji oni misle
da treba da budu predstavljeni.
da treba da budu predstavljeni.
06:49
For example,
159
397000
2000
Na primer,
06:51
the anecdote that some present,
160
399000
2000
anegdota koju neki pričaju jeste
06:53
as Captain so-and-so
161
401000
2000
da je neki kapetan
06:55
observed lots of fish in this area
162
403000
3000
posmatrao mnogo riba u ovoj oblasti
06:58
cannot be used
163
406000
2000
koje se ne mogu koristiti
07:00
or is usually not utilized by fishery scientists,
164
408000
3000
ili ih ne koriste naučnici za proučavanje riba,
07:03
because it's not "scientific."
165
411000
2000
jer to nije "naučno".
07:05
So you have a situation
166
413000
2000
Time dobijate situaciju
07:07
where people don't know the past,
167
415000
3000
da ljudi nisu upoznati sa prošlošću,
07:10
even though we live in literate societies,
168
418000
3000
iako živimo u pismenim zajednicama
07:13
because they don't trust
169
421000
2000
jer ne veruju
07:15
the sources of the past.
170
423000
3000
izvorima iz prošlosti.
07:18
And hence, the enormous role
171
426000
3000
To je velika uloga
07:21
that a marine protected area can play.
172
429000
2000
koju igra zaštićena pomorska oblast.
07:23
Because with marine protected areas,
173
431000
3000
Jer u pomorski zaštićenim oblastima
07:26
we actually recreate the past.
174
434000
4000
ponovo stvaramo prošlost.
07:30
We recreate the past that people cannot conceive
175
438000
3000
Stvaramo prošlost koju ljudi ne mogu ni da zamisle
07:33
because the baseline has shifted
176
441000
2000
jer se osnova pomerila
07:35
and is extremely low.
177
443000
2000
i nalazi se veoma nisko.
07:37
That is for people
178
445000
2000
To je za ljude
07:39
who can see a marine protected area
179
447000
5000
koji mogu da posmatraju te zaštićene oblasti
07:44
and who can benefit
180
452000
2000
i koji mogu da imaju koristi
07:46
from the insight that it provides,
181
454000
3000
od uvida u situaciju
07:49
which enables them to reset their baseline.
182
457000
4000
i to im omogućava da reše ovaj problem.
07:53
How about the people who can't do that
183
461000
2000
Šta je sa ljudima koji ne mogu to da urade
07:55
because they have no access --
184
463000
2000
jer nemaju pristup --
07:57
the people in the Midwest for example?
185
465000
3000
ljudi sa Srednjeg zapada, na primer?
08:00
There I think
186
468000
2000
Moguće je
08:02
that the arts and film
187
470000
2000
da umetnost i filmovi
08:04
can perhaps fill the gap,
188
472000
2000
ispune ovu prazninu
08:06
and simulation.
189
474000
2000
i simulaciju.
08:08
This is a simulation of Chesapeake Bay.
190
476000
3000
Ovo je simulacija Česepik zaliva.
08:11
There were gray whales in Chesapeake Bay a long time ago --
191
479000
2000
U Česepik zalivu je pre mnogo godina
bilo sivih kitova,
bilo sivih kitova,
08:13
500 years ago.
192
481000
2000
pre 500 godina.
08:15
And you will have noticed that the hues and tones
193
483000
3000
Primetićete da su boje slične onima
08:18
are like "Avatar."
194
486000
2000
kao u filmu "Avatar".
08:20
(Laughter)
195
488000
2000
(Smeh)
08:22
And if you think about "Avatar,"
196
490000
2000
Ako pomislite na taj film,
08:24
if you think of why people were so touched by it --
197
492000
3000
ako se zapitate zašto su ljudi bili toliko oduševljeni,
08:27
never mind the Pocahontas story --
198
495000
4000
bez obzira na priču o Pokahontas,
08:31
why so touched by the imagery?
199
499000
4000
zašto su te slike uticale na nas?
08:35
Because it evokes something
200
503000
3000
Zato što to izaziva nešto u nama,
08:38
that in a sense has been lost.
201
506000
2000
kao osećaj da smo nešto izgubili.
08:40
And so my recommendation,
202
508000
2000
Od svih saveta koji mogu da vam dam,
08:42
it's the only one I will provide,
203
510000
2000
jedan jedini ću podeliti sa vama,
08:44
is for Cameron to do "Avatar II" underwater.
204
512000
5000
a to je da Kameron snimi "Avatar 2" ispod vode.
08:49
Thank you very much.
205
517000
2000
Hvala najlepše.
08:51
(Applause)
206
519000
2000
(Aplauz)
ABOUT THE SPEAKER
Daniel Pauly - Fisheries biologistDaniel Pauly is the principal investigator at the Sea Around Us Project, which studies the impact of the world's fisheries on marine ecosystems. The software he's helped develop is used around the world to model and track the ocean.
Why you should listen
Daniel Pauly heads the Sea Around Us Project, based at the Fisheries Centre, at the University of British Columbia. Pauly has been a leader in conceptualizing and codeveloping software that’s used by ocean experts throughout the world. At the Sea Around Us and in his other work, he’s developing new ways to view complex ocean data.
Pauly’s work includes the Ecopath ecological/ecosystem modeling software suite; the massive FishBase, the online encyclopaedia of fishes; and, increasingly, the quantitative results of the Sea Around Us Project.
Daniel Pauly | Speaker | TED.com