Impact of Global Fisheries and Global Warming - PowerPoint PPT Presentation

Loading...

PPT – Impact of Global Fisheries and Global Warming PowerPoint presentation | free to download - id: 3dd5a0-OWQzN



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Impact of Global Fisheries and Global Warming

Description:

Impact of Global Fisheries and Global Warming on Marine Ecosystems and Food Security Daniel Pauly Sea Around Us Project Fisheries Centre, UBC A Future for Fisheries? – PowerPoint PPT presentation

Number of Views:209
Avg rating:3.0/5.0
Slides: 68
Provided by: vlizBedo
Learn more at: http://www.vliz.be
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Impact of Global Fisheries and Global Warming


1
Impact of Global Fisheries and Global Warming on
Marine Ecosystems and Food Security
Daniel Pauly Sea Around Us Project Fisheries
Centre, UBC
A Future for Fisheries? Toward Effective
Strategies for Sustainability KU Leuven,
February 5, 2008
2
This graph, illustrating a Canadian tragedy,
leads to several questions. One of them is how
typical is the story of the Northern cod fishery?
Can we generalize?
And it goes on!
3
We can define
Fully exploited
Developing



Over-exploited
Underdeveloped
Crashed
Now lets apply these definitions to the global
FAO catch statistics
4
Our first generalization is bleak indeed.
Crashed
Over-exploited
Fully exploited
Stocks ()
Developing
Underdeveloped
5
Also, it is tempting to project these trends
Stocks ()
2048 ?
6
Our next generalization relies on maps. We dont
really know where most fisheries operate, but
when we have global FAO catch statistics, we can
infer the distribution of fisheries (and of
catches) by using a filtering approach
7
Taxon (what)
FAO Area (where)
Country (who)
Taxon Distribution Database
Spatial Reference Database
Fishing Access Database
Over 99.9 of the global marine catch can be
assigned to ½ degree spatial cells, and we are
steadily improving the underlying databases
No improve underlying databases
Common Spatial Cells?
YES
Assign catch rates to cells
8
This is the first map we got. It was not very
exciting, except for the anomalies (red).
0
We had no problem with Peruvian and Chilean
waters being extremely productive. But China?
9
Thus, global fisheries landings, despite (or
because of ) increasing effort, have been
declining since the late 1980s, a fact long
hidden by over-reporting from China
Watson and Pauly (Nature), 2001.
10
In fact, the decline is even stronger if one
considers discarded fish. This was generally
overlooked when FAOs last estimate of discards
(dot E 7-8 million t) was released.
Discarded fishes and invertebrates
Other landed fishes and invertebrates
Peruvian anchoveta
Zeller and Pauly (Fish Fisheries, 2005)
11
Back to basics ecosystem fluxes move up trophic
pyramids
and each species tends to have its own trophic
level
12
Another generalization emerges when we compute
the mean trophic level of world catches. This
shows a global decline
Pauly et al. (Science, 1998)
13
In fact, fishing down is so widespread that the
Convention on Biological Diversity (CBD) now uses
mean trophic levels as an index of biodiversity,
the Marine Trophic Index.
Trophic level change (1950-2000)
0.5 to 1.0
gt1
no change /no data
14
And this means that fishing down is everywhere
15
We can see from space how trawlers stir up
sediment
Here shrimp trawlers off the Texas Coast, Gulf
of Mexico
  • Photo courtesy of Dr. Kyle van Houten (Duke
    University)

16
The Benguela Current may be the first system
where jellyfish became dominant, but it wont be
the last
17
Consumers in the North have not noticed this,
nor similar trends while most seafood is traded
between the EU, the USA and Northeast Asia, the
South has so far met the shortfall in the
North.
18
Well need to get out of the vicious circle of
contemporary fisheries management.
19
We can do things right, as illustrated by Georges
Bank haddock
Emergency Closure
200-Mile Limit
20
Now turning to subsidies
How subsidies induce overfishing
Lets assume a Gordon-Schaefer bioeconomic model
21
Global subsidy comparisons
Sumaila and Pauly (2006)
22
Subsidies come in different flavors
Sumaila and Pauly (2006)
23
Marine Protected Areas are part of the solution.
There are many, but most of them are tiny
1 of world ocean area (growth rate 5 year-1)




Wood et al. (in press)
24
As a result, the growth of the global MPA network
is so slow that we will miss all the targets
Wood et al. (in press)
25
Aquaculture has grown to a production of 40
millions t in the last decades , and some
believe it is solution to our fish supply problem
Freshw. fishes
However, all the optimistic projections forget
that aquaculture is mainly a Chinese enterprise
(2/3 of production), devoted mainly to freshwater
fishes
China
26
But a major trend in aquaculture is what may be
called farming up the food web, which occurs in
major producing countries
Note absence of an increasing trend for the USA,
due to a high production of (low trophic level)
catfishes (Pauly et al. 2001. Conservation
Biology in Practice 2(4) 25).
The farms impacts on coastal ecosystems are,
besides pollution, that they tend to increase the
fishing down effects
27
One approach much talked about are market-based
mechanisms, see e.g., www.seafoodguide.org.
Another approach is illustrated here
Photo (?) by Jennifer Jacquet
Jacquet, J. and D. Pauly. 2007. The rise of
consumer awareness campaigns in an era of
collapsing fisheries. Mar. Pol. 31 315-321.
28
However, over 1/3 of the worlds fish catch is
currently wasted, i.e., turned into animal feeds
36
Source Watson, Alder Pauly, 2006
29
which is a tremendous waste of good food
30
Meanwhile, thing are heating up
Al Gore IPCC Nobel Prize 2007
..
31
Temperature-abundance profile
Probability of occurrence by water temperature
Small yellow croaker (Larimichthys polyactis)
Relative abundance
Low
High
32
Small yellow croaker
Year 0
33
Small yellow croaker
Year 30
34
Barndoor skate (Dipturus laevis)
Year 0
Relative abundance
Low
High
35
Barndoor skate (Dipturus laevis)
Year 2
Relative abundance
Low
High
36
Barndoor skate (Dipturus laevis)
Year 4
Relative abundance
Low
High
37
Barndoor skate (Dipturus laevis)
Year 6
Relative abundance
Low
High
38
Barndoor skate (Dipturus laevis)
Year 8
Relative abundance
Low
High
39
Barndoor skate (Dipturus laevis)
Year 10
Relative abundance
Low
High
40
Barndoor skate (Dipturus laevis)
Year 12
Relative abundance
Low
High
41
Barndoor skate (Dipturus laevis)
Year 14
Relative abundance
Low
High
42
Barndoor skate (Dipturus laevis)
Year 16
Relative abundance
Low
High
43
Barndoor skate (Dipturus laevis)
Year 18
Relative abundance
Low
High
44
Barndoor skate (Dipturus laevis)
Year 20
Relative abundance
Low
High
45
Barndoor skate (Dipturus laevis)
Year 22
Relative abundance
Low
High
46
Barndoor skate (Dipturus laevis)
Year 24
Relative abundance
Low
High
47
Barndoor skate (Dipturus laevis)
Year 26
Relative abundance
Low
High
48
Barndoor skate (Dipturus laevis)
Year 28
Relative abundance
Low
High
49
Barndoor skate (Dipturus laevis)
Year 30
Relative abundance
Low
High
50
Greenland shark (Somniosus microcephalus)
Year 0
Relative abundance
Low
High
51
Greenland shark (Somniosus microcephalus)
Year 2
Relative abundance
Low
High
52
Greenland shark (Somniosus microcephalus)
Year 4
Relative abundance
Low
High
53
Greenland shark (Somniosus microcephalus)
Year 6
Relative abundance
Low
High
54
Greenland shark (Somniosus microcephalus)
Year 8
Relative abundance
Low
High
55
Greenland shark (Somniosus microcephalus)
Year 10
Relative abundance
Low
High
56
Greenland shark (Somniosus microcephalus)
Year 12
Relative abundance
Low
High
57
Greenland shark (Somniosus microcephalus)
Year 14
Relative abundance
Low
High
58
Greenland shark (Somniosus microcephalus)
Year 16
Relative abundance
Low
High
59
Greenland shark (Somniosus microcephalus)
Year 18
Relative abundance
Low
High
60
Greenland shark (Somniosus microcephalus)
Year 20
Relative abundance
Low
High
61
Greenland shark (Somniosus microcephalus)
Year 22
Relative abundance
Low
High
62
Greenland shark (Somniosus microcephalus)
Year 24
Relative abundance
Low
High
63
Greenland shark (Somniosus microcephalus)
Year 26
Relative abundance
Low
High
64
Greenland shark (Somniosus microcephalus)
Year 28
Relative abundance
Low
High
65
Greenland shark (Somniosus microcephalus)
Year 28
Relative abundance
Low
High
66
Antarctic toothfish (Dissostichus mawsoni)
Original (static) distribution
Distribution after 30 years
Relative abundance
Low
High
as an example of a species predicted to go
extinct
67
Acknowledgements
  • Thanks to the Pew Charitable Trusts,
    Philadelphia
  • Fisheries Centre, University of British Columbia
  • Members of the Sea Around Us project,

and many others...
visit us at www.seaaroundus.org
About PowerShow.com