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Keywords:

  • data collection;
  • global community of practitioners;
  • Google Earth;
  • inland fisheries assessment

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

Abstract  The majority of the global inland fisheries catch is obtained in developing countries. However, there are severe constraints in collection of information on inland fisheries leading to doubts over the reliability of the available information at the global and regional scales. A major constraint of data collection is the dispersed characteristics of inland fisheries, which cannot be covered by traditional approaches. Sample-based monitoring of inland fisheries with an appropriate sample frame will improve the present information on inland fisheries. However, it is argued that further rapid improvement of available information can be obtained by providing assessment tools to a global community of practitioners. One such a tool, a combination of databases making use of Google Earth, analysed in a GIS platform and yield modelling is presented and discussed.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

Inland capture fisheries are rooted in socially and culturally complex societies. They operate in a large variety of environments and are characterised by an extremely diverse range of gears. Inland fisheries are generally labour intensive and in most cases do not easily lend themselves to mechanisation and industrialisation. They are thus typically driven by individual human effort and the overall number of people in the fishery. As a result they are not generally great wealth creators for individual fishers but may, in aggregate, be massive suppliers of food, labour and income. Within a changing world, it will be a major challenge to sustain the different functions of inland fisheries such as their role in food security and poverty alleviation and other ecosystem service. They do not, however, usually provide an opportunity for taxation, resulting in little incentive to invest already scarce human and financial resources into collecting information needed for policy development and management of inland fisheries. This paper provides a summary of some of the constraints in inland fisheries data collections and explores some ideas on how to do better.

The official statistic – Inland waters

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

Globally, lakes, reservoirs and wetlands cover a total surface area of about 7.8 million km2 and are important inland fisheries (Table 1). Relatively high proportions of land are covered with surface waters in SE Asia, North America, East and Central West Africa, the northern part of Asia, Europe and South America. A large part of the water bodies lie in the colder north and are not very productive (Fig. 1; Welcomme 2011). In 2008, Members of the Food and Agriculture Organisation of the United Nations (FAO) reported 10.2 million tonnes of production from inland fisheries; the majority of production came from developing countries (Table 2), and the biggest single contribution from the Mekong River (Welcomme et al. 2010). However, these data are acknowledged as being inaccurate (Coates 2002; Allan et al. 2005; Welcomme et al. 2010; Welcomme 2011; WorldBank, FAO & WorldFish Center 2010).

Table 1. Distribution by continent of major surface freshwater resources (Lehner & Döll 2004)
ContinentSurface area in km2Total%
LakesReservoirsRiversFloodplainFlooded forestPeat landIntermittent wetland
Asia898 00080 000141 0001 292 00057 000491 000357 0003 316 00042
North America861 00069 00058 00018 00057 000205 00026 0001 294 00017
Africa223 00034 00045 000694 000179 000 187 0001 362 00017
Europe101 00014 000500053 000 13 000500186 5002
South America90 00047 000108 000422 000860 000 28001 529 80020
Australia80004000500   112 000124 5002
Oceania5000100010006000  10013 1000.2
TOTAL2 186 000249 000358 5002 485 0001 153 000709 000685 4007 825 900100
image

Figure 1.  Freshwater coverage and reported inland fisheries production in kg ha−1 of freshwater area.

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Table 2. Distribution of inland fisheries catch in developing and rich countries (based on FAO FishStat 2008)
Low income food deficient country status (LIFDC)Production 2008 (tonnes)Percentage of productionWater area (km2)Percentage of water surface
LIFD countries6 528 000651 967 00025
Non-LIFD countries3 557 000355 862 00075
WorldBank – income status
 Low4 175 000411 222 00016
 Lower middle4 903 000491 589 00020
 Upper middle812 00083 493 00045
 High194 00021 516 00019
WorldBank – development status
 Developing9 078 000902 811 00036
 Developed1 006 000105 009 00064

Although statistics are improving in some countries, collecting accurate information on inland fisheries can be extremely costly. Moreover, many public administrations still do not collect such information or make assessments of the status of inland fishery resources. The very nature of inland fisheries makes assessment of their status extremely difficult. In addition, inland fisheries practised for sustenance or gain often take place in remote areas and are carried out by the poorer sectors of society. Catches are frequently not recorded by species or not recorded at all. Catch statistics are generally inadequate for use as a measure of stock status, therefore providing accurate statements on the status of inland fishery resources on a global or even regional level remains a challenge (FAO FishStat 2008).

In 2003, FAO Member States committed themselves to improving such statistics by adopting the Strategy for Improving Information on the Status and Trends of Capture Fisheries. This strategy was subsequently endorsed by the United Nations General Assembly later that year. In addition, the BigNumbers study recently carried out by WorldBank, FAO & WorldFish Center (2010) estimated total inland fisheries production at 15 million tonnes, and identified inland fisheries are mainly small scale, providing employment to 61 million person of which 50% are women (Table 3). The production estimates of this study, based on case studies and extrapolation to the global level, were 50% higher than the official reported figures. The study did not include subsistence or recreational fishing and, consequently, the official reported production of inland fisheries could be seriously underestimated (FAO 1999, 2003, Allan et al. 2005; Welcomme et al. 2010; Welcomme 2011).

Table 3. Some characteristics of small-scale and large-scale inland fisheries (WorldBank, FAO & WorldFish Center 2010)
Production and utilisationSmall scaleLarge scaleTotal
Total annual catch (million tonnes)14115
Value (billion US$)90.69.6
Annual catch for domestic human consumption (million tonnes)12113
Annual catch for domestic human consumption as share of total catch (%)0.90.91.8
Employment (million fulltime and part-time)
 Number of fishers (million)19.40.820.2
 Number of jobs in post-harvest (million)40.70.341.0
 Total workforce (million)60161
 % of women in total workforce54%28% 
 Catch (tonnes fisher−1 yr−1)0.71.3 

Why do we need information on inland fisheries?

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

Knowledge of the status and trends of inland fisheries is key to sound policy development, better decision-making and responsible fisheries management. It is necessary at the national level for the maintenance of food security and for describing social and economic benefits of fisheries. Such information is also essential for assessing the validity of fisheries policy, for tracking the performance of fisheries management and for assessing impacts of developments in other sectors of the economy on fisheries.

There is now broad agreement at the international policy level that the ecosystem approach to fisheries (EAF) is the appropriate and necessary framework for fisheries management: an ecosystem approach to fisheries strives to balance diverse societal objectives, by taking account of the knowledge and uncertainties about biotic, abiotic and human components of ecosystems and their interactions and applying an integrated approach to fisheries within ecologically meaningful boundaries (FAO 2003).

Inland fisheries management needs an ecosystem approach (Bartley et al. 2012), and this is particularly important in large catchment areas for large lakes and river systems. There is therefore a need to specify information requirements, data collection and the ecosystem approach to fisheries management. For large lakes and river systems, the entry point for EAF could be the biological dimension and essential information requirements could be more targeted to this dimension. In view of the high poverty rates and dependency of fisheries for daily protein intake, the high levels of subsistence and seasonal fishing in large floodplains and wetlands with open access, the entry point for EAF could be more related to the human dimensions, requiring more information on the social, economic and institutional aspects of inland fisheries.

Constraints in data collection

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

It is extremely difficult, if not impossible, to estimate the production from inland fisheries using the same approaches as those used to assess marine fisheries. The majority of inland fisheries are not licensed; they operate at commercial, semi-commercial and subsistence levels, and are widely dispersed along the lengths of all rivers and streams as well as in a variety of water bodies and wetlands. There are often no centralised landing ports or major markets where data can be easily collected, and a large part of the catch is bartered locally or consumed by the fisher and his/her household. Catch size and composition, gears used and the number of fishers vary greatly by season. Therefore, data should ideally be collected several times per year, and over a number of years, but poorly developed infrastructure in remote areas makes the collection of data both time-consuming and expensive.

Furthermore, as few fees or taxes can be levied on these fisheries, there is little incentive to invest already scarce human and financial resources to collect the data. The institutional capacity to collect and analyse the data remains low in many countries and one of the results is that trends in catches become suppressed because data are aggregated across basins and species. Often, landings are recorded for some indicative fisheries and these are subsequently extrapolated up to a national figure, with large errors occurring if structural data (e.g. numbers of gears, numbers of fishers, numbers of households involved) are unreliable. Chronic problems of insufficient human and financial resources allocated for data collection or inefficient data collection schemes have often resulted in poor quality of information that further led to non-limited or limited use of statistics for fishery management and policy development. Consequently, only dwindling support was given to systematic improvement of national fishery data and information collection systems. These challenges point to the urgent need to terminate this vicious cycle of problems, and to do this, there is the need to explore the key constraints and alternative approaches.

Alternative approaches

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References

Sample-based surveys

The dispersed nature of small-scale inland fisheries implies that they can only be covered through sample-based surveys. The foundation of a sample-based survey is the sample frame used to design the sampling scheme and to estimate values of variables for the target fishery. Statistical procedures for sample-based fisheries surveys are well described (e.g. Caddy & Bazigos 1985; Sparre & Venema 1998; Stamatopoulos 2002; Cadima et al. 2005). For the larger water bodies dominated by professional fishers, sample-based surveys can be applied, but capacity building in sample design and the application of sample-based surveys is essential as often the statistical procedures are violated because of budgetary and staff limitations, leading to statistically invalid results.

The structural information on the number, characteristics and spatial distribution of vessels, gears, fishers, landing sites and fishing communities constituting the sampling frame is traditionally obtained through a frame survey or fisheries census (Bazigos 1974). Frame surveys should be updated regularly, but this often does not happen because of the high costs involved, leading to unreliable total estimates. In some cases, external funding may be required to conduct these projects.

Another main bottleneck of the sampling frame is the lack of information on how many people/households are engaged in subsistence fisheries. Structural information on subsistence fisheries cannot be obtained through frame surveys. The only way to obtain a sampling frame on subsistence fisheries is to make use of external resources (e.g. to include fisheries-related questions in census such as population census or agriculture census, conducted by other (non-fishery) institutions; Crispoldi 2003; WorldBank 2011).

Using geographic information systems (GIS)

In sample-based surveys, production (Y) is traditionally calculated as the product of catch-per-unit-effort (CPUE) and the fishing effort f as: Y = CPUE × f. In marine small-scale fisheries, this is often a valid method as both CPUE and effort are relatively easy to establish. However, for many inland fisheries this is not the case. The bulk of the catch is taken by dispersed small-scale fishers, the fishing activities are of an informal nature, and they operate in remote rural areas. Part-time fishing is the norm, especially mixed farming/fishing lifestyles on floodplains. Furthermore, the range of gears used makes it impossible to standardise any measure of CPUE. Most inland fisheries harvest is consumed domestically and much of it within the communities where the fishing occurs (Coates 2002). Considering that global coverage of fresh water (water bodies >10 ha) is 7.8 million km2 or more, it is doubtful if inland fisheries can be monitored completely through sample-based surveys.

An alternative approach could be making use of global models and Geographic Information Systems (GIS) to estimate global inland fisheries production. Yield modelling in inland fisheries is not new; in the 1950s and 1960s, equations using linear regression were developed relating morphometric and edaphic factors to fish yields in temperate lakes and reservoirs. Fish production in Canadian lakes was inversely related to mean depth (Rawson 1952), to water chemistry (Moyle 1956) and to physical and chemical indices (Northcote & Ryder 1965). Ryder (1965) combined these indices to make a morpho-edaphic index (MEI) (total dissolved solids divided by mean depth) in 23 temperate lakes. In the 1970s and early 1980s, these models were applied to a selected number of African inland waters. MEI was related to yields from African tropical lakes and reservoirs (Henderson & Welcomme 1974) and from Lake Bangweulu System (Toews & Griffith 1979). Youngs and Heimbuch (1982) showed that area is a powerful predictor of catch. Their catch versus area model was first applied to 17 African lakes and reservoirs by Marshall (1984). Similar models have been advanced for catch from rivers as a function of their length or basin area in different continents and standard yields derived per unit area of floodplain (Welcomme 2001).

Welcomme (2011) used the global number of lakes of different areas estimated by Downing et al. (2006) and the area model (yield = 160 × lake area0.24) to estimate the global inland lake fisheries at 93 million tonnes. He noted the shortcomings of this estimate however: The area model is based on a tropical set, whereas many of the higher latitude lakes will have lower yields, be used for recreation or not fished at all. Nevertheless they do indicate to possibility of serious underestimation of actual catches world wide and The true purpose of the estimation is to illustrate the high proportion of inland waters that are small lakes with individually insignificant levels of catch. Their physical dispersion and large numbers makes them virtually impossible to sample and, as a result, models have to be used to estimate their total catch from a more restricted sample. However, because of the large numbers of water bodies and watercourses involved, comparatively small changes in the model can greatly change the magnitude of the estimates. There is, therefore a need for much basic research both of the numbers of water bodies and watercourses in various parts of the world...

In the last decade, considerable progress has been made towards available global information on size and classification of water bodies through the Global Lakes and Wetlands Database (Lehner & Döll 2004) and the African Water Resource Database (Jenness et al. 2007a,b). However, results of yield modelling are rather old; basic research on variability of yield patterns, its geographical distribution patterns, validity of yield models in relation to river basins or freshwater ecoregions and exploring the reliability of the models is essential.

The developments of GIS, the availability of public online satellite images, data sets of water bodies, rainfall, population density and temperature may allow development of more sophisticated ways of yield modelling, which could lead to better estimates of global inland fisheries landings. In GIS, a number of spatial layers, for example annual catch per hectare, average rainfall, average temperature, population density, can be combined and analysed with a spatial multi-linear regression tools to develop spatial yield models for estimation of actual landings by type of water body. A first step would be to obtain and combine the different layers at a global or regional scale.

Global water database

Lehner and Döll (2004) published a Global Lakes and Wetlands Database (GLWD). The database is publicly available and contains geo-referenced data on water bodies larger than 10 ha. The database can be used and analysed directly in the most common GIS software package. An example of a quick analysis is presented in Figure 1, where the freshwater coverage (in percentage of total land area) and the reported inland fisheries production (in kg ha−1 of freshwater area) are displayed for all countries. The results highlight the geographical differences in production levels indicated by Welcomme et al. (2010). The large area of freshwater in the northern hemisphere, where production levels are rather low, may limit overall estimates of catch.

Google Earth

Google Earth displays satellite images of varying resolution of the Earth’s surface, allowing users to zoom in to specific items, water bodies or villages they want to see. Google Earth has a standard global coverage of satellite images, but additional GIS files can be imported in Google Earth as an overlay. By zooming in and clicking on the water body, the different types of water bodies can be easily identified through inbuilt pop-ups.

From a software point of view, the pop-up function in Google Earth could be modified in such a way that data for the identified water bodies, such as number of fishers, annual production, main species, can be added. In a second step, the data provided in the pop-up could be sent to a central data base and used in the development of global layers on inland fisheries, modelling and rapid assessments of value. To be functional, basic key indicators on all types of water bodies need to be added and be related to physical characteristics of the water body, production and socio economics.

Creating a global expert community

A tool using Google Earth and the GLWD to identify and data collected on water bodies does not exist. However, experiences of the FAO FishCode STF and the BigNumbers study indicated that more information is available at local level than is reported at national or at global level. Making better use of this local information could lead to better knowledge of the value of inland fisheries. It will not replace the global statistics or national data collection system, it will only draw upon local available expert information (validated or non-validated) and bring this together in a global or in regional platform(s). The way forward could be the creation of an online global expert community on inland fisheries information using this proposed tool.

For catch estimates, the lake area model to predict inland fisheries production (Welcomme 2011) was based on a database of 450 lakes much of which is now old. Similarly, the river models were based on surveys from as far back as the 1970s. Therefore, larger, contemporaneous data sets will be needed to develop the more sophisticated regional and/or global models needed for the assessment. This can only be achieved through a coordinated programme involving the collaboration of a large community of fisheries scientists and managers, data collectors, social scientists and all those involved in studying small-scale inland fisheries.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. The official statistic – Inland waters
  5. Why do we need information on inland fisheries?
  6. Constraints in data collection
  7. Alternative approaches
  8. References
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