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The Bioeconimic Seaweed Model (BESeM) For Modelling Kappaphycus Cultivation in Indonesia - Dr. Pepijn van Oort


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The Bioeconimic Seaweed Model (BESeM) For Modelling Kappaphycus Cultivation in Indonesia - Dr. Pepijn van Oort

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Thanks for this interesting presentation Dr. van Oort. We have been doing this sort of modeling for quite a while now, so it is good to see other approaches being applied.

I am interested in how you factor societal factors into your modeling, since it is not only revenue quantity but also revenue distribution that impacts farming strategies.

For example, we did trials around Bantaeng and Bulukumba in the IFC-PENSA project (2004-2008) that showed much better return per unit cost/effort when bibit about 150-200 (or even as much as 500) grams were used as starting material, compared to when small bibit about 20-40 grams were used. Despite that, farmers persisted in using the very small bibit. The reason given, was that village ladies were paid on a piecework basis per planted line to attach bibit. Smaller bibit means more lines must be planted … hence more income to the ladies. In fact, the size of harvested fronds in much of SulSel was smaller that the size of poropagules typically planted around Zamboanga, Philippines.

I guess that optimization is in the eye of the beholder …


On another issue…. we find that expressing farm productivity by area (e.g. per square meter) is less relevant that productivity per length of planted line (or tubenet) because farmers typically do not pay for usage of sea area, but capital cost is correlated with length of planted substrate.

During our field visits we asked the ladies about initial planting weights. Farmers reported to us planting 20 kg fresh weight per 25m line, that gives 20/25 = 0.8kg = 800 g/m. With plants at 20cm that is 5 plants/m, so an individual plant would be 800/5 = 40g, that is the same as you are mentioning here.

We did not measure in every site the distance between lines. Consider a standard line of 25m and parallel lines at Lw = 0.8 m distance from each other implies 1 m line per 0.8*1.0 m2 square sea surface, that is 1/0.8 = 1.25 m line / m2 sea surface. A measured yield of 1000 g/m corresponds with 1000*(1/Lw) = 1250 g/m2. A simulated yield of 1000 g/m2 corresponds with 1000*Lw = 800 g/m line. As we can see, the conversion is simple, requiring only the additional measurement of Lw. Surprisingly, reporting of line spacing Lw is not common practice in seaweed research, which is one of the issues making it difficult to compare experiments.


Dear Iain

Thanks for your elaborate comment. I can see you closely watched our video and appreciate your comments.

The most important thing about our presentation is to present an approach. We are still quite uncertain about many of the numbers. We did visit Sulawesi, talked with stakeholders and read the literature. Much is still unknown.  We present income at optimum planting density and cycle length, but as we are quite uncertain about farmgate prices, and uncertain about fixed and variable costs, also we are uncertain about the resulting net income. For the biological parameters we are conducting an experiment, which will allow for estimating the biological parameters. For the economic parameters, we are still thinking about how to more accurately estimate these.

I agree with you about expressing yield per meter line. Farmers would normally express yield in fresh weight or semi-dry weight per meter line. In the biological sciences, we would convert this to seaweed dry weight (0%) per m2 or kg carrageenan / m2. The advantage of the farmer way of reporting is that it is intuitive to interpret to stakeholders. A disadvantage is that it is not standardized, i.e. it is less straight forward to compare productivity between different experiments if experiments have different line density (m line / m2) or where moisture content differs between species or experiments. Opposite case for the more scientific approach: more standardised but less intuitive. We do measure line density and moisture content, which allows us to present yields in both ways.

Thank you for comments on the income and income distribution and on how ladies are being paid. Basically, our approach has been to make the model as simple as possible while still capturing the essentials of the production system. Of course this is open for debate, I'm happy to listento anyone saying we missed something essential in the model, and happy to learn more about the socio-economics of the production system.

Like to hear more about your work, perhaps later after the conference we could have a 1-1 chat?

All the best,



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