Mission Blue Voyage
Daniel Pauly: The ocean's shifting baseline
Daniel Pauly: Promjena osnove oceana
Filmed:
Readability: 3.8
254,411 views
Ocean se razgradio tijekom našeg životnog vijeka, što je prikazano smanjivanjem prosječne veličine ribe. I svejedno, što nam Daniel Pauly pokazuje na pozornici Mission Bluea, svaki put kad osnovica padne, mi ju zovemo novom „normalom“. Kada ćemo prestati pomicati granicu prema dolje?
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
Pričat ću
00:14
about a tiny, little idea.
1
2000
3000
o jednoj sitnoj ideji.
00:17
And this is about shifting baseline.
2
5000
4000
I to o promjeni osnove.
00:21
And because the idea can be explained in one minute,
3
9000
4000
Kako ta ideja može biti objašnjena u jednoj minuti,
00:25
I will tell you three stories before
4
13000
3000
prije nje ću vam ispričati tri priče
00:28
to fill in the time.
5
16000
2000
da popunim vrijeme.
00:30
And the first story
6
18000
2000
Prva priča je
00:32
is about Charles Darwin, one of my heroes.
7
20000
3000
o Charlesu Darwinu, jednom od mojih heroja.
00:35
And he was here, as you well know, in '35.
8
23000
3000
On je bio ovdje, kao što svi dobro znate, u '35.
00:38
And you'd think he was chasing finches,
9
26000
2000
I mislili biste da je tražio zebe,
00:40
but he wasn't.
10
28000
2000
ali nije.
00:42
He was actually collecting fish.
11
30000
2000
Ustvari je sakupljao ribu.
00:44
And he described one of them
12
32000
2000
I jednu od njih je opisao
00:46
as very "common."
13
34000
2000
kao jako "uobičajenu".
00:48
This was the sailfin grouper.
14
36000
2000
To je bila Mycteroperca olfax.
00:50
A big fishery was run on it
15
38000
2000
Do '80-ih su je
00:52
until the '80s.
16
40000
3000
mnogo lovili.
00:55
Now the fish is on the IUCN Red List.
17
43000
3000
Sada je ta riba na IUCN-ovom (Međunarodni savez za očuvanje prirode) crvenom popisu.
00:58
Now this story,
18
46000
2000
Ta priča,
01:00
we have heard it lots of times
19
48000
3000
čuli smo je puno puta
01:03
on Galapagos and other places,
20
51000
2000
na Galapagosu i ostalim mjestima
01:05
so there is nothing particular about it.
21
53000
3000
pa nije ništa posebno.
01:08
But the point is, we still come to Galapagos.
22
56000
3000
Ali poanta je, svejedno dolazimo na Galapagos.
01:11
We still think it is pristine.
23
59000
3000
Još uvijek mislimo da je nedirnut.
01:14
The brochures still say
24
62000
3000
Brošure još uvijek kažu
01:17
it is untouched.
25
65000
2000
da je netaknut.
01:19
So what happens here?
26
67000
3000
Što se događa ovdje?
01:22
The second story, also to illustrate another concept,
27
70000
3000
Druga priča, također da ilustriram jedan drugi koncept,
01:25
is called shifting waistline.
28
73000
2000
zove se promjena obujma struka.
01:27
(Laughter)
29
75000
3000
(Smijeh)
01:30
Because I was there in '71,
30
78000
2000
Zato što sam proučavao lagunu
01:32
studying a lagoon in West Africa.
31
80000
2000
u Zapadnoj Africi '71.
01:34
I was there because I grew up in Europe
32
82000
3000
Bio sam tamo jer sam odrastao u Europi
01:37
and I wanted later to work in Africa.
33
85000
2000
i želio sam kasnije raditi u Africi.
01:39
And I thought I could blend in.
34
87000
2000
I pomislio sam da ću se uspjeti uklopiti.
01:41
And I got a big sunburn,
35
89000
2000
Zadobio sam veliku opekotinu od sunca
01:43
and I was convinced that I was really not from there.
36
91000
3000
i bio sam uvjeren da nisam zapravo od tamo.
01:46
This was my first sunburn.
37
94000
2000
To je bila moja prva opekotina.
01:48
And the lagoon
38
96000
3000
Laguna je
01:51
was surrounded by palm trees,
39
99000
2000
bila okružena palmama,
01:53
as you can see, and a few mangrove.
40
101000
2000
kao što možete vidjeti, i par mangrova.
01:55
And it had tilapia
41
103000
2000
Imala je tilapije
01:57
about 20 centimeters,
42
105000
2000
duge oko 20 centimetara,
01:59
a species of tilapia called blackchin tilapia.
43
107000
2000
vrstu tilapije koja se zove crnobradata tilapija.
02:01
And the fisheries for this tilapia
44
109000
2000
Ribolov na tilapije
02:03
sustained lots of fish and they had a good time
45
111000
3000
sadržavao je mnoštvo ribe i dobro e išao
02:06
and they earned more than average
46
114000
2000
te se zaradilo više nego u prosjeku
02:08
in Ghana.
47
116000
2000
u Gani.
02:10
When I went there 27 years later,
48
118000
3000
Kada sam otišao tamo 27 godina kasnije,
02:13
the fish had shrunk to half of their size.
49
121000
3000
riba se smanjila na pola svoje veličine.
02:16
They were maturing at five centimeters.
50
124000
2000
Sazrijevale su s pet centimetra.
02:18
They had been pushed genetically.
51
126000
2000
Potaknute su genetski.
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 ribari su još uvijek na neki način bili sretni.
02:24
And the fish also were happy to be there.
54
132000
5000
I ribe su bile sretne što su tamo.
02:29
So nothing has changed,
55
137000
2000
Ništa se nije promijenilo,
02:31
but everything has changed.
56
139000
2000
ali sve se promijenilo.
02:33
My third little story
57
141000
2000
Moja treća pričica jest
02:35
is that I was an accomplice
58
143000
2000
da sam bio suučesnik
02:37
in the introduction of trawling
59
145000
2000
početaka kočarenja
02:39
in Southeast Asia.
60
147000
2000
u južnoistočnoj Aziji.
02:41
In the '70s -- well, beginning in the '60s --
61
149000
3000
U 70-ima – pa, s početkom u 60-ima –
02:44
Europe did lots of development projects.
62
152000
3000
Europa je radila na mnogo razvojnih projekata.
02:47
Fish development
63
155000
2000
Unaprijeđenje ribarstva
02:49
meant imposing on countries
64
157000
2000
je značilo nametanje
02:51
that had already 100,000 fishers
65
159000
3000
industrijskog ribarstva
02:54
to impose on them industrial fishing.
66
162000
3000
na zemlje koje već imaju 100 000 ribara.
02:57
And this boat, quite ugly,
67
165000
2000
Brod se zvao, prilično ružno,
02:59
is called the Mutiara 4.
68
167000
2000
Mutiara 4.
03:01
And I went sailing on it,
69
169000
2000
Plovio sam se na njemu,
03:03
and we did surveys
70
171000
3000
i istraživali smo
03:06
throughout the southern South China sea
71
174000
3000
cijelu južnu stranu Južnog kineskog mora,
03:09
and especially the Java Sea.
72
177000
2000
a posebno Javansko more.
03:11
And what we caught,
73
179000
2000
Ostali smo bez riječi
03:13
we didn't have words for it.
74
181000
2000
zbog onoga što smo uhvatili.
03:15
What we caught, I know now,
75
183000
3000
Sada znam, da je ono što smo uhvatili
03:18
is the bottom of the sea.
76
186000
2000
bilo dno mora.
03:20
And 90 percent of our catch
77
188000
2000
90 posto našeg ulova
03:22
were sponges,
78
190000
2000
bile su spužve,
03:24
other animals that are fixed on the bottom.
79
192000
3000
ostale životinje koje su čvrsto na dnu.
03:27
And actually most of the fish,
80
195000
2000
I zapravo, većina ribe,
03:29
they are a little spot on the debris,
81
197000
2000
bile su male točke smeća,
03:31
the piles of debris, were coral reef fish.
82
199000
3000
hrpe smeća, bile su ribe koraljnih grebena.
03:34
Essentially the bottom of the sea came onto the deck
83
202000
2000
U biti, dno mora se diglo na palubu
03:36
and then was thrown down.
84
204000
2000
i onda bilo bačeno dolje.
03:38
And these pictures are extraordinary
85
206000
3000
Ove slike su izvanredne
03:41
because this transition is very rapid.
86
209000
3000
jer je taj prijelaz veoma brz.
03:44
Within a year, you do a survey
87
212000
3000
U jednoj godini, napraviš istraživanje
03:47
and then commercial fishing begins.
88
215000
2000
i onda komercijalno ribarstvo počinje.
03:49
The bottom is transformed
89
217000
2000
Dno je promijenjeno
03:51
from, in this case, a hard bottom or soft coral
90
219000
3000
iz, u ovom slučaju, tvrdog dna ili mekanog koralja
03:54
into a muddy mess.
91
222000
3000
u blatni nered.
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
Nisu pojedene, bačene su, zato što su mrtve.
04:02
And one time we caught a live one.
94
230000
2000
Jednom smo uhvatili živu kornjaču.
04:04
It was not drowned yet.
95
232000
2000
Još se nije utopila.
04:06
And then they wanted to kill it because it was good to eat.
96
234000
3000
I onda su je htjeli ubiti jer je bila jestiva.
04:09
This mountain of debris
97
237000
3000
Ovu planina smeća
04:12
is actually collected by fishers
98
240000
3000
ustvari skupe ribari
04:15
every time they go
99
243000
2000
svaki put kada odu
04:17
into an area that's never been fished.
100
245000
2000
u područje u kojem se još nije lovilo.
04:19
But it's not documented.
101
247000
2000
Ali to nije dokumentirano.
04:21
We transform the world,
102
249000
2000
Mijenjamo svijet,
04:23
but we don't remember it.
103
251000
2000
ali to ne pamtimo.
04:25
We adjust our baseline
104
253000
3000
Pomičemo osnovicu
04:28
to the new level,
105
256000
2000
na novu razinu,
04:30
and we don't recall what was there.
106
258000
4000
a ne sjećamo se što je bilo tamo.
04:34
If you generalize this,
107
262000
2000
Ako generaliziramo,
04:36
something like this happens.
108
264000
2000
nešto takvo se događa.
04:38
You have on the y axis some good thing:
109
266000
3000
Na y osi imamo neke dobre stvari:
04:41
biodiversity, numbers of orca,
110
269000
3000
biološku raznolikost, broj orki,
04:44
the greenness of your country, the water supply.
111
272000
3000
zelenilo u državi, zalihu vode.
04:47
And over time it changes --
112
275000
2000
I s vremenom se to mijenja.
04:49
it changes
113
277000
2000
Mijenja se
04:51
because people do things, or naturally.
114
279000
2000
jer ljudi sve rade prirodno.
04:53
Every generation
115
281000
2000
Svaka generacija
04:55
will use the images
116
283000
2000
će koristiti slike
04:57
that they got at the beginning of their conscious lives
117
285000
3000
koje su dobili na početku svog svjesnog života
05:00
as a standard
118
288000
2000
kao standard
05:02
and will extrapolate forward.
119
290000
2000
i procijenit će vrijednost dalje.
05:04
And the difference then,
120
292000
2000
I razliku će tada vidjeti
05:06
they perceive as a loss.
121
294000
2000
kao gubitak.
05:08
But they don't perceive what happened before as a loss.
122
296000
3000
Ali ne primjećuju što se dogodilo prije kao gubitak.
05:11
You can have a succession of changes.
123
299000
2000
I možete imati slijed promjena.
05:13
At the end you want to sustain
124
301000
3000
Na kraju želite zadržati
05:16
miserable leftovers.
125
304000
3000
jadne ostatke.
05:19
And that, to a large extent, is what we want to do now.
126
307000
3000
I to je to ono što želimo napraviti sada.
05:22
We want to sustain things that are gone
127
310000
3000
Želimo zadržati stvari koje su nestale
05:25
or things that are not the way they were.
128
313000
4000
ili stvari koje više nisu kakve su bile.
05:29
Now one should think
129
317000
2000
Čovjek bi trebao misliti
05:31
this problem affected people
130
319000
2000
da je ovaj problem pogodio ljude
05:33
certainly when in predatory societies,
131
321000
4000
u predatorskim društvima,
05:37
they killed animals
132
325000
2000
ubijali su životinje
05:39
and they didn't know they had done so
133
327000
2000
i nisu znali što su napravili
05:41
after a few generations.
134
329000
2000
generacijama dalje.
05:43
Because, obviously,
135
331000
3000
Očito,
05:46
an animal that is very abundant,
136
334000
5000
životinja koje ima u velikom broju,
05:51
before it gets extinct,
137
339000
3000
prije nego izumre,
05:54
it becomes rare.
138
342000
3000
postane rijetka vrsta.
05:57
So you don't lose abundant animals.
139
345000
3000
Ne izgubite vrste kojih ima mnogo.
06:00
You always lose rare animals.
140
348000
2000
Uvijek izgubite one koje su rijetke.
06:02
And therefore they're not perceived
141
350000
2000
I tako nisu gledane
06:04
as a big loss.
142
352000
2000
kao veliki gubitak.
06:06
Over time,
143
354000
2000
S vremenom
06:08
we concentrate on large animals,
144
356000
2000
se koncentriramo na velike životinje,
06:10
and in a sea that means the big fish.
145
358000
2000
a u moru to znači velike ribe.
06:12
They become rarer because we fish them.
146
360000
3000
Postanu rijetke jer ih lovimo.
06:15
Over time we have a few fish left
147
363000
2000
S vremenom nam ostane nekoliko riba
06:17
and we think this is the baseline.
148
365000
3000
i mi mislimo da je to osnova.
06:20
And the question is,
149
368000
2000
Pitanje je:
06:22
why do people accept this?
150
370000
5000
Zašto ljudi to prihvaćaju?
06:27
Well because they don't know that it was different.
151
375000
3000
Zato što ne znaju da je bilo drugačije.
06:30
And in fact, lots of people, scientists,
152
378000
3000
I zapravo, mnogo ljudi, znanstvenika,
06:33
will contest that it was really different.
153
381000
2000
osporavati će da je to potpuno drugačije.
06:35
And they will contest this
154
383000
2000
A osporavat će to zato što
06:37
because the evidence
155
385000
2000
zato što dokaz koji
06:39
presented in an earlier mode
156
387000
5000
koji je prikazan ranije,
06:44
is not in the way
157
392000
3000
nije onakav
06:47
they would like the evidence presented.
158
395000
2000
kakav bi oni htjeli da je prikazan.
06:49
For example,
159
397000
2000
Na primjer,
06:51
the anecdote that some present,
160
399000
2000
anegdota koju neki prikazuju,
06:53
as Captain so-and-so
161
401000
2000
kapetan taj-i-taj
06:55
observed lots of fish in this area
162
403000
3000
opazio je mnogo ribe u tom području,
06:58
cannot be used
163
406000
2000
znanstvenici ribarstva
07:00
or is usually not utilized by fishery scientists,
164
408000
3000
ne mogu to iskoristiti,
07:03
because it's not "scientific."
165
411000
2000
jer nije "znanstveno".
07:05
So you have a situation
166
413000
2000
Dakle, imate situaciju
07:07
where people don't know the past,
167
415000
3000
gdje ljudi ne znaju prošlost,
07:10
even though we live in literate societies,
168
418000
3000
iako živimo u pismenom društvu,
07:13
because they don't trust
169
421000
2000
jer ne vjeruju
07:15
the sources of the past.
170
423000
3000
izvorima prošlosti.
07:18
And hence, the enormous role
171
426000
3000
I stoga, ogromna je uloga
07:21
that a marine protected area can play.
172
429000
2000
koju zaštita mora može igrati.
07:23
Because with marine protected areas,
173
431000
3000
Zato što sa zaštitom područja mora,
07:26
we actually recreate the past.
174
434000
4000
mi zapravo ponovno stvaramo prošlost.
07:30
We recreate the past that people cannot conceive
175
438000
3000
Ponovno stvaramo prošlost koju ljudi ne mogu shvatiti,
07:33
because the baseline has shifted
176
441000
2000
zato što se osnova promijenila
07:35
and is extremely low.
177
443000
2000
i ekstremno je niska.
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 vidjeti zaštićeno područje mora
07:44
and who can benefit
180
452000
2000
i koji se mogu okoristiti
07:46
from the insight that it provides,
181
454000
3000
uvidom koji pruža,
07:49
which enables them to reset their baseline.
182
457000
4000
što im omogućuje da ponovno postave svoju osnovu.
07:53
How about the people who can't do that
183
461000
2000
Što s ljudima koji to ne mogu napraviti
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 primjer?
08:00
There I think
186
468000
2000
Mislim da tamo
08:02
that the arts and film
187
470000
2000
to može nadomjestiti
08:04
can perhaps fill the gap,
188
472000
2000
umjetnost, film
08:06
and simulation.
189
474000
2000
i simulacija.
08:08
This is a simulation of Chesapeake Bay.
190
476000
3000
Ovo je simulacija Chesapeake zaljeva.
08:11
There were gray whales in Chesapeake Bay a long time ago --
191
479000
2000
Prije mnogo vremena u Chesapeake zaljevu postojali su sivi kitovi --
08:13
500 years ago.
192
481000
2000
prije 500 godina.
08:15
And you will have noticed that the hues and tones
193
483000
3000
I možete primijetiti da su boje i nijanse
08:18
are like "Avatar."
194
486000
2000
kao u "Avataru".
08:20
(Laughter)
195
488000
2000
(Smijeh)
08:22
And if you think about "Avatar,"
196
490000
2000
Ako razmislite o "Avataru",
08:24
if you think of why people were so touched by it --
197
492000
3000
ako razmislite zašto su ljudi toliko dirnuti njime –
08:27
never mind the Pocahontas story --
198
495000
4000
zanemarite priču o Pocahontas –
08:31
why so touched by the imagery?
199
499000
4000
zašto su toliko dirnuti izgledom?
08:35
Because it evokes something
200
503000
3000
Zato što on budi nešto
08:38
that in a sense has been lost.
201
506000
2000
što je izgubljeno.
08:40
And so my recommendation,
202
508000
2000
Pa je moja preporuka,
08:42
it's the only one I will provide,
203
510000
2000
jedina koju ću dati,
08:44
is for Cameron to do "Avatar II" underwater.
204
512000
5000
da Cameron napravi "Avatar II" pod vodom.
08:49
Thank you very much.
205
517000
2000
Puno vam hvala.
08:51
(Applause)
206
519000
2000
(Pljesak)
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