The State of World Fisheries and Aquaculture 2020


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PART 3 
OUTLOOK AND EMERGING ISSUES
FIGURE 58
BASIN-LEVEL THREAT MAPS FOR IMPORTANT INLAND FISHERIES
SOURCE: Unpublished data from US Geological Survey, Land and Water Lab at the University of Florida.
A.
MEKONG
ZAMBEZI
NILE
C.
B.
0 100 200
400
kilometres
0 150 300
600
kilometres
0
75
150
300
kilometres
THREAT SCORE
N/A
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| 182 |


THE STATE OF WORLD FISHERIES AND AQUACULTURE 
2020
Such waterbodies will require a separate threat 
analysis for the waterbody itself.
Figure 58
presents four basin-level threat maps 
for important inland fisheries in Africa and 
Asia. The sub-basin disaggregation shows how 
different parts of a basin may contribute to its 
overall threat level. The different levels may be 
due to a high concentration of impacts in some 
areas, but not in others. It emphasizes that not 
all parts of basin are affected in the same way, 
and this has implications for both fisheries and 
biodiversity in each of these subareas. 
An important feature of these threat maps is 
that they are scalable, ranging from the global 
map (
Figure 57
) through to basin and sub-basin 
scales (
Figure 58
) and to even lower resolution 
where the data exist. This allows fisheries and 
environmental managers to examine threats 
and drivers at the level appropriate to their 
management plans, and it supports an ecosystem 
approach to fishery management. 
The advantage of this mapping method is that 
it uses global, publicly available data, allowing 
coverage of countries that may have very limited 
capacity to collect and report data to FAO. 
The interpretation of the maps can be greatly 
enhanced by triangulating the results of threat 
maps with field observations based on local 
knowledge and data collection, something that 
FAO and its Members could seek to strengthen. 
Linking the threat maps to fishery data at a 
subnational level will enable more detailed 
national analysis and planning, especially 
pointing to areas where there is a need for 
greater understanding of primary threats and 
their relationship to fisheries production and 
fish biodiversity. This would enable national 
fishery agencies to identify important inland 
fisheries (or aquatic biodiversity) that are at risk 
and prioritize appropriate fishery monitoring 
and management interventions. 
The mapping could also be used to select and 
track some key inland fisheries as indicator 
fisheries, for a replicable assessment of the 
changes in global inland fisheries production. 
Such assessments could initially be supported 
by holistic fishery evaluation approaches, 
which aim to capture fishery status without 
the requirement for intensive sampling 
programmes. Linking an understanding of 
the state of the selected inland fisheries to the 
global threat map would also provide a baseline 
and means to report meaningfully on progress 
towards international goals such as the Aichi 
Biodiversity Targets on inland fish stocks, 
as well as action on ecosystem restoration to 
support the SDGs. 
Ultimately, this work will require commitment 
and additional resources to undertake 
assessments of the indicator fisheries on a routine 
basis, and agreement to report into a common 
framework in order to enable FAO to collate a 
global assessment in a similar manner to that of 
the FAO marine stock status assessment. 
n
NEW AND DISRUPTIVE 
TECHNOLOGIES FOR 
INNOVATIVE DATA 
SYSTEMS AND PRACTICES 
The 2018 edition of 
The State of World 
Fisheries and Aquaculture
outlined the need 
to improve the availability and use of fishery 
data, statistics and information (FAO, 2018a). 
While the fisheries and aquaculture sector 
has historically lagged behind in terms of 
adoption of efficient information systems, 
increased attention is now focusing on the 
opportunities that innovations in information 
technologies can provide, and on how these 
can change the way fisheries and aquaculture 
sustainability issues are generated, interpreted 
and communicated (FAO, 2020f). New tools 
building on proven technologies such as mobile 
phones or cloud-based systems are being 
deployed to address some of the persistent 
weaknesses (
Box 23
). However, the irruption 
of new and emerging technologies – such as 
high-resolution satellite imagery, the Automatic 
Identification System (AIS), cameras and 
in situ
sensors, DNA and genetic profiling, blockchain, 
the Internet of Things (IoT), big data, artificial 
intelligence (AI) and machine learning – is 
likely to significantly affect the established 
data supply chain and disrupt the sector’s 
management in the short-to-medium term. 

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