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Environmental variability, effort development and the regenerative capacity of the fish stocks in Lake Chilwa, Malawi - P.A.M. van Zwieten and F. Njaya


In between recessions[17], Lake Chilwa is one of the most productive freshwater lakes in Malawi with a fishery production of between 80 and 160 kg/ha resulting in a long-term annual average catch of around 15 000 metric tonnes. The lake has an important bearing on the nutrition of Malawians, in particular within the nearby districts of Zomba, Phalombe and Machinga. The contribution of its fishery to the total fish catch of Malawi ranges between 16 percent and 43 percent, with an average of 22 percent (Figure 1A). Lake Chilwa is shallow, not exceeding 6m depths at peak levels. It has an open water area of around 678 km2 surrounded by about 600 km2 of Typha swamps, 390 km2 of marshes and 580 km2 of inundated floodplain. Early commentators already noted that fish yields were not constant and seemed to depend on lake-water levels (Hickling, 1942; Lowe, 1952; Furse et al., 1979). In good years, the annual catch can approach up to 25 000 metric tonnes, but drops below 10 000 tonnes are not uncommon. Lake Chilwa has shown large fluctuations in catch and effort since 1845, with periods where fishing stopped completely when the Lake dried up (Nicholson, 1998; McCracken, 1987). In addition to seasonal cycles of about 0.8-1.0 m, water levels fluctuated annually around 2-3 m which sometimes led to complete desiccation of the lake. For instance, during and after the 1995 recession, fishing operations were suspended on Lake Chilwa for two years (Figure 1B). Shortly after refilling and stabilization of water levels fishing resumed. Complete recessions have been recorded for about six times (Table 1). Spectral analysis of a time-series of water levels from 1949 to 1976 indicated a periodicity of very low water levels of around six years, explaining around 30 percent of the total variance in lake levels (Lancaster, 1979).

TABLE 1. Historical and observed lake level changes in Lake Chilwa




Very Low (dry)




O’Neill, 1884


Buchanan, 1893


Buchanan, 1893


O’Neill 1884


Drummond, 1902


Chipeta, 1972; Duff 1906


------------ Chipeta, 1972 ------------


------------ Garson & Campbell-Smith, 1958

Late 1930s

Burgess (pers. comm)


Chipeta, 1972


Chipeta, 1972


Kalk, 1979


Kalk, 1979


Kalk, 1979


Kalk, 1979 (highest)


Njaya, 1996

Source: Kalk, McLachlan and Howard-Williams (1979) see references there; Njaya (1996).

FIGURE 1 A. Total catch from Lake Chilwa as a proportion of the total catch of Malawi. B. Total catch of Lake Chilwa broken down by species and species groups. In 1976 and 1977 no breakdown to species is available. In 1996 and 1997 the lake dried up completely. For 1998 only nine months of data are available.

How do fish populations react to the recurrent recessions of the lake? The dominant commercial fish species are the endemic Oreochromis shiranus chilwae (Makumba), and the ubiquitous Barbus paludinosus (Matemba) and Clarius gariepinus (Mlamba): typical representatives of the three species groups that survive in highly dynamic systems (Leveque, 1995, 1997). Kalk (1979) gave an account of the fate of the three species in a comprehensive study on the biological effects of recessions before and after the 1968 major recession. Between 1965 and 1968, as the lake dried up, Oreochromis catches declined severely, Barbus catches initially increased but dropped in the last year and Clarias fishing only stopped in 1968, the year of complete drought. During a recession, remnants of the fish stocks find refuge in the mouths of larger inflowing rivers and in deeper lagoons, where water remains. These stocks appear to serve as a nucleus for a natural restocking of the lake after refilling: Clarias populations, as reflected in the catches, recovered in two years, Barbus in three years and Oreochromius after four to five years.

As fish stocks in Chilwa have exhibited an enormous regenerative capacity shown time and again after lake level recessions, the value of MSY estimates based on steady state assumptions of environmental stability can be questioned. The annual variation the lake ecosystem exhibits in fish production, points to a fisheries management approach primarily directed to the protection of remnant stocks during periods of recession and immediately after refilling of the lake, while populations are rebuilding. Therefore the issue of what sustainable levels of fishing effort are is relevant only to the period in between recessions. In the literature on Lake Chilwa different points of view exist on this matter. Furse (in: Kalk 1979, p.228) asserts that detrimental effects due to fishing when water-levels are high seem unlikely because: “stocks that can recover in two to three years from virtual annihilation by drought are never likely to be overfished to the point of disappearance”. He recommended maximizing catches in between recessions. On the other hand, in the same book, Kalk (1979, p.422) contends that a limit on the minimum mesh size of gillnets in normal years is needed. This “demonstrably protected the breeding stocks of Oreochromis species, without seriously affecting the catch of “other” species”, thus implying that fishing could have a detrimental effect on fish production levels of Lake Chilwa.

Since 1976 Malawi has a well established Catch and Effort Data Recording System (CEDRS) to monitor this fishery. Data collections as carried out in practice sometimes have been criticized severely to the extent that the information obtained was considered not useful to answer questions on the efficiency of the fishery and predict future developments through formal stock assessment methods. Attempts to determine maximum sustainable levels of production and associated effort levels have failed (Tweddle, Alimoso and Sodzabanja, 1994), and the unsatisfactory notion exists that the system could be overexploited while effort levels keep on increasing without being able to point out what would or could be sustainable levels of efficiency. Nevertheless, data are still being collected, mainly for the purpose of establishing total catch and effort levels. In this paper we will show that, despite their apparent deficiencies, this may be a severe under utilization of the information contained in the data collected that are still useful for management purposes.

Information that could be derived from the time series of catch and effort is not limited to formal stock-assessment methods. An analysis of trends and variability in catches and catch-rates, can produce empirical relationship, which can be used to predict - not necessarily when something happens but what happens if something changes. This will lead to knowledge of what can be perceived on the basis of which expectations can be formulated. The only long-term time series of catch and effort data of Lake Chilwa collected in a systematic way is through the CEDRS. Our present study aims to address, with the present Malawian catch and effort data, the possibility of detecting changes in fish stocks as a result of changes in fishing activity (effort) under the typical cycles of recession and subsequent refilling of Lake Chilwa. The emphasis is on the usage of catch and effort data as they exist in Malawi and the information contained in them to answer questions on effects of natural changes and changes in fishing effort. We will examine the potential to draw conclusions on observed trends in catch-rates - which are considered as an index of fish-stock levels - and relate these to trends in effort and water levels. In this report we will not examine the sources of error and bias that are present in the data collected through the existing CEDRS.[18] For this we refer to Weyl et al. (1999), who makes a number of recommendations for improving data collection and handling.

[17] The word recession in this text refers to periods with low to very low lake water levels.
[18] Problems outlined by Alimoso (1988), Stamatopoulos (1990) and Weyl et al. (1999) are:

a. The CEDRS does not take into account gear distribution and the way the gears are operated. Consequently, significant fishing activities may take place without being recorded: relatively rare gears which make large catches e.g. Matemba seines in Lake Chilwa, may result in severe under or overestimation of daily catches.

b. The use of raising factors in view of actual fishing operations: e.g. some methods use two boats and since the raising factor is based on the ratio of the number of fishing craft in the minor stratum to that of the sampled fishing beach during the sampling exercise catches are overestimated.

c. CAS data forms are complex, leading to recording errors. The manual transfers of data from form to form and the manual calculations, which follow, have been shown to be responsible for significant errors in the accepted statistics.

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