Last year a global disturbance of weather patterns disrupted harvests in many of the world's important agricultural areas. Worldwide production...
GMAT Critical Reasoning : (CR) Questions
Last year a global disturbance of weather patterns disrupted harvests in many of the world's important agricultural areas. Worldwide production of soybeans, an important source of protein for people and livestock alike, was not adversely affected, however. Indeed, last year's soybean crop was actually slightly larger than average. Nevertheless, the weather phenomenon is probably responsible for a recent increase in the world price of soybeans.
Which of the following, if true, provides the strongest justification for the attribution of the increase in soybean prices to the weather phenomenon?
Passage Analysis:
Text from Passage | Analysis |
Last year a global disturbance of weather patterns disrupted harvests in many of the world's important agricultural areas. |
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Worldwide production of soybeans, an important source of protein for people and livestock alike, was not adversely affected, however. |
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Indeed, last year's soybean crop was actually slightly larger than average. |
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Nevertheless, the weather phenomenon is probably responsible for a recent increase in the world price of soybeans. |
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Argument Flow:
The argument starts by establishing that bad weather hurt global agriculture, then shows that soybeans were actually unaffected and even did better than average. Finally, it presents the surprising conclusion that this same weather probably caused soybean prices to rise anyway.
Main Conclusion:
The weather phenomenon is probably responsible for a recent increase in the world price of soybeans.
Logical Structure:
This creates a puzzle - we have evidence that soybean production was healthy and above average, yet the author concludes that weather problems still caused price increases. The argument seems incomplete because it doesn't explain how weather that didn't hurt soybean production could still drive up soybean prices. We need additional information to bridge this gap and make the conclusion logical.
Prethinking:
Question type:
Strengthen - We need to find information that makes the conclusion more believable. The conclusion claims that weather disruption caused soybean prices to rise, even though soybean production wasn't hurt and was actually above average.
Precision of Claims
The argument makes specific quantitative claims: soybean production was 'not adversely affected' and was 'actually slightly larger than average.' The conclusion is about a 'recent increase in the world price of soybeans' being caused by the 'weather phenomenon.'
Strategy
We need to find scenarios that explain how weather disruption could cause soybean prices to rise even when soybean production increased. The key insight is that soybean prices don't just depend on soybean supply - they also depend on demand for soybeans and the availability of substitute protein sources. If the weather hurt other protein sources, demand for soybeans would increase, driving up prices despite good soybean harvests.
This choice tells us that anchovies, which provide important protein for livestock, had disrupted harvests due to the weather phenomenon. This creates a perfect logical bridge for our argument. When anchovies became scarce due to weather damage, livestock farmers would need alternative protein sources and would increase their demand for soybeans. Even though soybean supply was above average, this surge in demand from livestock farmers seeking protein alternatives would drive soybean prices up. This directly strengthens the conclusion by showing how weather disruption could cause soybean price increases despite good soybean harvests.
This choice tells us that soybean-producing countries had above-average harvests of other food crops too. This information actually works against our conclusion rather than strengthening it. If other crops also did well despite the weather problems, it suggests the weather phenomenon wasn't that disruptive to agriculture in soybean-producing regions. This would make it less likely that the weather caused soybean price increases, so this weakens rather than strengthens our argument.
This choice points out that soybean prices also rose after a previous similar weather disturbance. While this shows a pattern of correlation between weather disturbances and soybean price increases, it doesn't explain the causal mechanism. We still don't understand why weather that doesn't hurt soybean production would cause price increases. This provides some support through historical precedent but doesn't give us the logical explanation we need to strongly justify the attribution.
This choice tells us that heavy rains from the weather phenomenon improved grazing pastures, allowing farmers to reduce their dependence on supplemental feed. This works against our conclusion because if farmers needed less supplemental feed (which would include soybeans), then demand for soybeans would decrease, not increase. Lower demand should lead to lower prices, not higher prices, so this actually contradicts the idea that weather caused soybean price increases.
This choice provides background information that soybean prices had been falling for several years before last year. While this shows that the recent price increase represents a change in trend, it doesn't explain why the weather phenomenon would be responsible for this change. We still lack the causal mechanism connecting weather disruption to higher soybean prices despite good soybean harvests.