A POLARITY-ENERGY FOOD CHAIN TROPHIC CASCADE MODEL: IMPLICATIONS TO FISHERY MANAGEMENT

Celso C. Almirol, Vincent T. Lapinig, McNell O. Sabandal

Abstract


The paper developed a model that extends the classical Oksanen Polarity Theorem for simple food chains to accommodate the analyses of energy transfers from one trophic level to another. The Polarity-Energy Food Chain Trophic Cascade model developed is then used in the analysis of data obtained by researchers for sardines (Sardinella lemuru) and lake herring (Coregonous artedii). Results revealed that for the sardine population in the east coast of Siberut Island, a stable logistic population growth is observed. These information means that population of this pelagic fish species increases (as a function of time n) until it reaches a stable population if left on its own based on the logistic growth hypothesis. However, over-predation by the top level consumer (over-fishing) can disrupt this approach to stability (i.e. fishing intensity of δ > 14.5%) or if fish larvae are caught by very fine gill nets (i.e. causing a reduction in the value of r). Fishery closure during spawning period (September to October) up to March or April each year ensures sustainable catch for this fish species. On the other hand, for the population of lake herring in the Great Lakes displayed large fluctuations in both yield and effort. Data tend to support a growth rate r > 3.5 if a logistic growth model were used because of the observed chaotic fluctuations. This means that fishing has caused a decreased in fecundity (as reported) leading to a greater value of the growth rate r (ratio of average eggs per female to fecundity). Overall, the Polarity-Energy Food Chain Model developed supports temporary fishing ban or permanent identification of marine protected areas (MPA) to preserve the natural logistic growth patterns of economically-important fish species. In the former case, fishing is timed with the observed population periodicities while in the latter case, fishing can be allowed outside of the protected area which benefits from spill-over effects of the MPA.

Keywords


trophic cascades, food chains, food web, trophic levels, filter nets

Full Text:

PDF

References


Beschta, R.L. & Ripple, W.J. (2009). Large predators and trophic cascades in terrestrial ecosystems of the western United States. Biol. Conserv.,142, 2401– 2414.

Carpenter, S., Kitchell, J. and Hodg-son, J. (1985). Cascading trophic interactions and lake productivity. BioScience 35: 634- 639.

Cook, R. (1977). Raymond Lindeman and the trophic-dynamic concept in ecology. Science, 198 (4312), 22-26. doi: 10.1126/science.198.4312.22.

Ginanjar, M. (2006). Reproduction study of Lemuru (Sardinella lemuru Blk.) based on sexual maturity and fish length to predict spawning season at East Coast of Siberut Island. Abstract retrieved from IPB Bogor Agricultural University Scientific Repository. Indonesia.

Hairston N.G., Smith, F.E., and Slobodkin, L.B. (1960). Community structure, population control and competition. American Naturalist, 94, 421-425.

Jensen, A. (1984). Dynamics of fisheries that affect the population growth rate coefficient. Environmental Management, 8 (2), 135-140.

Jimenez, J., de Guzman, A., Jimenez, C. and Acuna, R. (2009). Panguil Bay fisheries over the decades: Status and management challenges. Journal of Environment and Aquatic Resources, 1 (1), 15-31.

Oksanen, L., Fretwell, S., Arruda, J., and Niemala, P. (1981). Exploitation ecosystems in gradients of primary productivity. American Naturalist, 118 (2), 240-261.

Pauly, D., Christensen, V., Walters, C. (2000). Ecopath, ecosim and ecospace as tools for evaluating ecosystem impact of fisheries. ICES J. Mar. Sci, 57 (3), 697–706.

Lindeman, R. (1942). The trophic dynamic aspect of ecology. Ecology, 23, 399-418

Russ, G.R., and Alcala, A.C. (1996). Do marine reserves export adult fish biomass? Evidence from Apo Island, Central Philippines. Marine Ecology Progress Series 132, 37265.


Refbacks

  • There are currently no refbacks.