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<h1><span>Subsistence
fisheries</span>
<span class="style1"><strong class="style12"> Current Status: </strong>
</span><span class="style24">Functional</span></h1>
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<h2 style="margin-top:32px">Definitions</h2>
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<h2 style="margin-top:32px">Module specifications</h2>
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<h5 class="style10" style="width: 609px">Case studies</h5>
<h5 class="style21" style="width: 609px">(1) Madagascar</h5>
<h5 class="style19" style="width: 609px"> </h5>
<h5 class="style10" style="width: 609px">E<span class="style14">xplanation</span></h5>
<p class="MsoNormal">Our initial fisheries models
focused on mapping only subsistence use of fisheries, as
opposed to their commercial or recreational value, which
can be modeled separately, as they would have different
beneficiary groups and flow characteristics (i.e., means
for their beneficiaries to reach and use the fishery
resource).<span> </span>Although recreational and
commercial fisheries are of great importance, their flow
models are likely to be more complex, requiring
accounting for trade networks and recreational choices
(described in more detail in the Chapter 8).<span>
</span>Subsistence fisheries by contrast only require an
understanding of the species and quantity of fish used
and the ability of users to access the resource, are
thus a logical starting point for modeling how
beneficiaries use and value fisheries.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<div class="style8">
<h5 class="style10">Assumptions</h5>
<p class="MsoNormal"><b>Subsistence fisheries source
value</b>.<span> </span>The data available to
establish the quantity of fish available for
subsistence and other fisheries use (and link this
to a flow model) are generally quite sparse.<span>
</span>As discussed above, we obtained global
relative abundance maps for four species of
commercial importance in Madagascar.<span>
</span>We also obtained historical catch data for
Madagascar from the FAO (2008).<span> </span>
These catch data do not explicitly describe
subsistence catch, however, and do not contain catch
records for any of the four species for which we
have relative abundance data.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Despite these limitations, we
can use these data, along with a series of
assumptions, to estimate the catch for each species
(i.e., its supply or source value).<span>
</span>Historical catch data from The Sea Around Us
Project (2010) shows that 71.6% of the total catch
for Madagascar from 1950-2004 is “non-identified
marine pelagic fishes.”<span> </span>In 2005,
Madagascar produced 138,477 tonnes of fish from
capture fisheries, of which 77,636 tonnes were for
commodity trade and production (FAO 2008).<span>
</span>Another 72,300 tonnes were taken by
traditional fishermen, however, this catch is not
necessarily mutually exclusive with the commodity
sector.<span> </span>Subtracting the commodity
catch from the total catch leaves 60,841 tonnes of
fish assumed to go toward local consumption.<span>
</span>Assuming 71.6% of the locally consumed fish
are “non-identified marine pelagic fishes,” these
would account for 43,562 tonnes in 2005.<span>
</span>Assuming that each of the three marine
pelagic fishes (<i>L. mahsena</i>, <i>L. variegatus</i>,
<i>L. argentimaculatus)</i> for which we have
distribution data accounted for 20% of that total,
this would give 8,712 tonnes of fish caught for each
of these species.<span> </span>Since southern
meagre (<i>A. hololepidotus)</i> is a demersal
species we do not include it in the totals or in
further fisheries mapping, since we have no data on
the catch of non-identified marine demersal fish
species.<span> </span>We the divide the total
catch for each species according to their relative
abundance along the Madagascar coast in order to
produce a map of subsistence fish production for
each species under the above assumptions (Equation
1).</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Mathematically, we can express
these assumptions as: </p>
<p class="MsoNormal"><span>
</span></p>
<p class="MsoNormal"><span>
</span>(1)<span> </span>S = a<sub>1</sub>S<sub>1</sub>
+ a<sub>2</sub>S<sub>2</sub> + a<sub>3</sub>S<sub>3</sub>
+ … + a<sub>n</sub>S<sub>n<span> </span></sub>
</p>
<p class="MsoNormal"><span>
</span>(2)<span> </span>D = a<sub>1</sub>S<sub>1</sub>
+ a<sub>2</sub>S<sub>2</sub> + a<sub>3</sub>S<sub>3</sub>
+ … + a<sub>n</sub>S<sub>n </sub><span> </span></p>
<p class="MsoNormal"><sub><o:p> </o:p></sub></p>
<p class="MsoNormal">Where<span> </span>S =
the total source or supply of subsistence fisheries
(kg)</p>
<p class="MsoNormal"><span>
</span>D = the total demand for subsistence
fisheries (kg)</p>
<p class="MsoNormal"><span>
</span>a = the percentage of the total demand met
with species n</p>
<p class="MsoNormal"><span>
</span>S = the total mass of species n caught (kg)</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">We thus make a series of
admittedly large assumptions based on the very
limited available data about the magnitude of supply
and demand in Madagascar’s subsistence fishery and
the distribution of valuable species.<span>
</span>However, given better data or expert
knowledge of the relative use of different species,
we need only to adjust the above coefficients in
order to more accurately describe human dependence
on Madagascar’s fisheries.<span> </span>Source
and use (or supply and demand) for fisheries are
both expressed in kg.<span> </span>This allows
us to use a common unit in the flow models to move a
certain number of kg of fish from areas where they
are caught by subsistence fishermen to places where
they are consumed by fishermen and their families
and communities.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Subsistence fisheries use</b>.<span>
</span>People are more likely to access fisheries
for subsistence purposes when they lack other
sources of nutrition (e.g., in poorer regions) and
when they have access to a fishery.<span>
</span>As determinants of subsistence fisheries use,
we used distance to the coast, poverty, and
population density as influences of the degree of
use (Figure 9).<span> </span>We expect the
greatest use of subsistence fisheries at lower
population densities (i.e., in large cities there is
too much crowding, water pollution, and lack of
access to fisheries to enable widespread subsistence
fishing), greater levels of poverty, and closer
proximity to the coast.<span> </span>In the
conditional probability table for subsistence
fisheries use, we assumed that areas that are not
proximate to the coast have zero subsistence
fisheries use, and that use increases at lower
population densities and greater poverty levels.<span>
</span>This model does not account for subsistence
fisheries from rivers and other inland water bodies,
which of course could occur in inland areas.<span>
</span>We assigned prior probabilities for distance
to coast, poverty, and population density based on
quantitative analysis of available GIS data for
Madagascar.<span> </span>We discretized
population density by natural breaks, percent
poverty by equal intervals, and distance to the
coast based on easily walkable distances (e.g., <1
km, 1-5 km, >5 km).<span> </span>We note that
fish could also be traded to groups located farther
from the coast, with the benefits extending further
inland.<span> </span>However, modeling of such
trade networks is currently beyond the scope of our
models.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The Bayesian network returns
likelihood values for subsistence marine fisheries
use.<span> </span>To convert this to total
demand, we note that the average Malagasy consumes
6.8 kg of fish per year (FAO 2008).<span>
</span>In areas with high subsistence use, we assume
100% of this per capita use to come from the oceanic
subsistence fishery.<span> </span>In areas
with moderate subsistence use, we assume 67% of this
total to come from the oceanic subsistence fishery
(4.6 kg/capita), and in areas with low subsistence
use we assume 33% of this total to come from the
oceanic subsistence fishery (2.3 kg/capita).<span>
</span>We assume that the remaining unsatisfied
demand from moderate and low subsistence users comes
from either trade or inland fisheries in rivers and
lakes.<span> </span>Similarly to mapping the
supply or source of subsistence fisheries, we assume
that each of the three valuable species supplies 20%
of the fish use for subsistence users (Equation 2).<span>
</span>This is an admittedly naïve assumption that
can be easily corrected by adjusting the model
coefficients to better reflect data or expert
knowledge of resource use.</p>
<span LANG="EN">
<p>
<img HEIGHT="208" SRC="img/BNN%20subsistence%20fisheries%20use%20in%20Madagascar.gif" WIDTH="571"></p>
</span>
<p class="MsoNormal"><b>Subsistence fisheries sinks</b>.<span>
</span>As an ecosystem good, subsistence fisheries
do not have a sink that depletes the flow of an
ecosystem good from ecosystems to people.<span>
</span>In other words, there are no anthropogenic or
biophysical features on the landscape that deplete
the quantity of caught fish as they are moved from
the point of extraction to the point of consumption.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Subsistence fisheries flow</b>.<span>
</span>Subsistence fisheries flow models are
designed to illustrate the spatial dependence of
fisheries users on particular fisheries areas.<span>
</span>Subsistence fisheries users are assumed to
move from a point of origin (their homes) to an
oceanic fishery, harvest fish, and return to their
homes, where fish are consumed, via road or path
networks.<span> </span>Thus the flow models
move a given quantity of kg of fish from the ocean
to areas of demand.<span> </span>Each coastal
ocean pixel has an estimated potential source of
fish, as described above in the source model.<span>
</span>Each pixel on land has an estimated potential
use for oceanic fish, as described above in the use
model.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">We assume that the use of
oceanic subsistence fisheries is greatest close to
the coast, and declines relatively quickly moving
inland.<span> </span>We model such distance
decay as an exponential curve, with high subsistence
use within 1 km of the coast, steep decline at
distances of 2-3 km of the coast, and slowly
declining subsistence use out to a distance of 5 km
of the coast.<span> </span>The distance decay
function is expressed in the conditional probability
table within the subsistence use Bayesian network,
where high coastal proximity translates into much
higher levels of subsistence fisheries use, holding
the other variables in the Bayesian network, poverty
and population density, constant.<span> </span>
Along with proximity, users must have some form of
access (e.g., roads, paths) to get to the coast,
river, or lake.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The flow models thus move a
quantity of fish (in kg) from the coastal ocean
toward inland users along a network of paths (the
predominant means of transportation in rural
Madagascar).<span> </span>As </p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Limitations, caveats, and
directions for future research</b>. Several large
assumptions are built into this model by necessity,
largely due to the limited amount of information
about fish populations, their locations, and levels
of subsistence fisheries use.<span> </span>
While the species distribution maps from The Sea
Around Us Project (Close et al. 2006) show the
relative distribution of each species, they do not
show populations or total abundance of each species
(clearly an intractable task for marine fisheries
biologists).<span> </span>We thus make
assumptions that the four modeled species...</p>
<p class="MsoNormal">These parameters could be
refined based on local data or expert assumptions
from those knowledgeable of Madagascar’s subsistence
fishing communities. </p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Modeling species change based
on local habitat quality data: should be done in
conjunction with locally knowledgeable experts.<span>
</span>Coupling flow models for current levels of
sedimentation and nutrient inputs to nearshore
habitats, and these impacts on habitats (Figure X):
</p>
<p class="MsoNormal">In the future: add nitrogen
runoff (Potter et al. in press)</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal">While we initially model only
four species, additional species could easily be
added to the model by inputting their distribution
maps.<span> </span></p>
<p class="MsoNormal"> </p>
<h5 class="style10">Spatial data</h5>
<p class="MsoNormal"> </p>
<table border="1" cellpadding="0" cellspacing="0" class="style17" style="mso-border-alt: solid black .5pt; mso-yfti-tbllook: 191; mso-padding-alt: 0pt 5.4pt 0pt 5.4pt; mso-border-insideh: .5pt solid black; mso-border-insidev: .5pt solid black">
<tr>
<td valign="top" width="101">
<p class="MsoNormal">
<strong class="style19">Model</strong></p>
</td>
<td valign="top" width="114">
<p class="MsoNormal">
<strong class="style19">Layer</strong></p>
</td>
<td valign="top" width="107">
<p class="MsoNormal">
<strong class="style19">Source</strong></p>
</td>
<td valign="top" width="103">
<p class="MsoNormal">
<strong class="style19">Resolution </strong>
</p>
</td>
<td valign="top" width="96">
<p class="MsoNormal">
<strong class="style19">Extent</strong></p>
</td>
<td valign="top" width="70">
<p class="MsoNormal">
<strong class="style19">Year</strong></p>
</td>
</tr>
<tr>
<td valign="top" width="101">
<p class="style19">Subsistence fisheries
source – Madagascar<o:p></o:p></p>
</td>
<td valign="top" width="114">
<p class="MsoNormal"><span class="style20">
A. hololepidotus, L. borbonicus, L. mahsena,
L. argentimaculatus</span><span class="style19">
relative abundance<o:p></o:p></span></p>
</td>
<td valign="top" width="107">
<p class="style19">Sea Around Us Project<o:p></o:p></p>
</td>
<td valign="top" width="103">
<p class="MsoNormal"><span class="style19">
0.5 degrees</span><span><sup class="style19">2</sup><o:p></o:p></span></p>
</td>
<td valign="top" width="96">
<p class="style19">Global<o:p></o:p></p>
</td>
<td valign="top" width="70">
<p class="style19">1950-2003<o:p></o:p></p>
</td>
</tr>
<tr>
<td rowspan="3" valign="top" width="101">
<p class="style19">Subsistence fisheries use
– Madagascar<o:p></o:p></p>
</td>
<td valign="top" width="114">
<p class="style19">Population density<o:p></o:p></p>
</td>
<td valign="top" width="107">
<p class="style19">LANDSCAN, Oak Ridge
National Lab<o:p></o:p></p>
</td>
<td valign="top" width="103">
<p class="style19">30 arc-second<o:p></o:p></p>
</td>
<td valign="top" width="96">
<p class="style19">Global<o:p></o:p></p>
</td>
<td valign="top" width="70">
<p class="style19">2006<o:p></o:p></p>
</td>
</tr>
<tr>
<td valign="top" width="114">
<p class="style19">Poverty<o:p></o:p></p>
</td>
<td valign="top" width="107">
<p class="style19">Elvidge et al. (2009)<o:p></o:p></p>
</td>
<td valign="top" width="103">
<p class="style19">30 arc-second<o:p></o:p></p>
</td>
<td valign="top" width="96">
<p class="style19">Global<o:p></o:p></p>
</td>
<td valign="top" width="70">
<p class="style19">2004<o:p></o:p></p>
</td>
</tr>
<tr>
<td valign="top" width="114">
<p class="style19">Distance to coast<o:p></o:p></p>
</td>
<td valign="top" width="107">
<p class="style19">BD500 (Madagascar
infrastructure data)<o:p></o:p></p>
</td>
<td valign="top" width="103">
<p class="style19">Vector line file<o:p></o:p></p>
</td>
<td valign="top" width="96">
<p class="style19">Madagascar (Ring buffer
around coastline)<o:p></o:p></p>
</td>
<td valign="top" width="70">
<p class="style19"><o:p> </o:p></p>
</td>
</tr>
<tr>
<td valign="top" width="101">
<p class="style19">Subsistence fisheries
flow - Madagascar<o:p></o:p></p>
</td>
<td valign="top" width="114">
<p class="style19">Paths<o:p></o:p></p>
</td>
<td valign="top" width="107">
<p class="style19">BD500 (Madagascar
infrastructure data)<o:p></o:p></p>
</td>
<td valign="top" width="103">
<p class="style19">Vector line file<o:p></o:p></p>
</td>
<td valign="top" width="96">
<p class="style19">Madagascar<o:p></o:p></p>
</td>
<td valign="top" width="70">
<p class="style19"><o:p> </o:p></p>
</td>
</tr>
</table>
<p class="MsoNormal">
<table border="1" cellpadding="0" cellspacing="0" class="style22" style="mso-border-alt: solid black .5pt; mso-yfti-tbllook: 191; mso-padding-alt: 0pt 5.4pt 0pt 5.4pt; mso-border-insideh: .5pt solid black; mso-border-insidev: .5pt solid black">
</table>
<table border="1" cellpadding="0" cellspacing="0" class="style20" style="mso-border-alt: solid black .5pt; mso-yfti-tbllook: 191; mso-padding-alt: 0pt 5.4pt 0pt 5.4pt; mso-border-insideh: .5pt solid black; mso-border-insidev: .5pt solid black">
</table>
</p>
<p class="style3"> </p>
<h5 class="style10">References</h5>
<p class="style23">Booth, D.B. and C.R. Jackson.<span>
</span>1997.<span> </span>Urbanization of
aquatic systems: Degradation thresholds, stormwater
detection, and the limits of mitigation.<span>
</span>Journal of the American Water Resources
Assocation 33 (5): 1077-1090. </p>
<p class="style23">Close, C., et al. 2006.<span>
</span>Distribution ranges of commercial fishes and
invertebrates.<span> </span>Fisheries Centre
Research Reports 14 (4): 27-37.</p>
<p class="style23">Elvidge, C.D., et al.<span>
</span>2009.<span> </span>A global poverty map
derived from satellite data.<span> </span>
Computers and Geosciences 35 (8): 1652-1660.</p>
<p class="style23">Food and Agriculture Organization
of the United Nations (FAO).<span> </span>
2008.<span> </span>Fishery Country Profile:
The Republic of Madagascar.
<a href="http://www.fao.org/fishery/countryprofiles/search/en">
http://www.fao.org/fishery/countryprofiles/search/en</a>.</p>
<p class="style23"><span>Froese, R. and D. Pauly.
Editors. 2010. FishBase. World Wide Web
electronic publication. www.fishbase.org, version
(01/2010).</span></p>
<p class="style23"><span>Potter, P., et al. In
press. Characterizing the spatial patterns of
global fertilizer application and manure production.
Forthcoming in: Earth Interactions.</span></p>
<span>
<a href="http://www.seaaroundus.org/eez/450.aspx">
The Sea Around Us Project.</a> 2010. Data and
visualization, EEZ waters of Madagascar. </span>
<h5 class="style10"> </h5>
<h5 class="style10">Additional contributors</h5>
<p class="style5">Fisheries data were supplied by William Cheung.<span>
</span>UNEP-WCMC supplied other marine biotic datasets.<span>
</span>Liz Selig and Carmen Lacambra provided guidance into
additional global marine datasets.</p>
<h4 style="margin-top:32px" class="style10"> </h4>
<br><br></div>
</td>
<td width="50%" class="style9"> </td>
</tr>
</table>
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