Michael Grieco
AP Biology
Current Event 2
20 September 2018
Curtis, Philip G., et al. “Classifying Drivers of Global Forest Loss.” Science, American
Association for the Advancement of Science, 14 Sept. 2018,
“Classifying Drivers of Global Forest Loss”
By Philip G. Curtis, Christy M. Slay, Nancy L. Harris, Alexandra Tyukavina, and Matthew C. Hansen
This article follows up on the development of a computer algorithm that classifies the factors of forest loss
for the entire globe. It is a public dataset that processed satellite pictures of the entire globe from Google
Earth, allowing companies, nongovernmental organizations, and governments to “provide visibility on
deforestation risk” (p. 1). The five classifications include: commodity-driven deforestation, shifting
agriculture, forestry, wildfire, and urbanization, which are the causes of 99% of forest loss across the
globe (p. 2). The article provides a summary of the data in a chart (Table 1, p. 2), that shows how previous
studies on this issue (which used a sample to extrapolate the causes across the globe) were quite inaccurate,
and had deviation between different scientists, creating uncertainty in actual numbers. This new study
provides accurate data concerning the main causes to forest loss. The main point of this article was that
the 450 companies committed to zero deforestation within their supply chains could not identify
accordingly for two reasons. One was due to the complexity of supply chains, especially for larger
corporations who have unclear locations. And the other is, even if the location was known, the existing
data concerning the amount of deforestation was inaccurate. And this new data set will allow companies
to accurately target their efforts. It also opens up new discussions concerning the conservation,
restoration, and management of forest ecosystems.
for the entire globe. It is a public dataset that processed satellite pictures of the entire globe from Google
Earth, allowing companies, nongovernmental organizations, and governments to “provide visibility on
deforestation risk” (p. 1). The five classifications include: commodity-driven deforestation, shifting
agriculture, forestry, wildfire, and urbanization, which are the causes of 99% of forest loss across the
globe (p. 2). The article provides a summary of the data in a chart (Table 1, p. 2), that shows how previous
studies on this issue (which used a sample to extrapolate the causes across the globe) were quite inaccurate,
and had deviation between different scientists, creating uncertainty in actual numbers. This new study
provides accurate data concerning the main causes to forest loss. The main point of this article was that
the 450 companies committed to zero deforestation within their supply chains could not identify
accordingly for two reasons. One was due to the complexity of supply chains, especially for larger
corporations who have unclear locations. And the other is, even if the location was known, the existing
data concerning the amount of deforestation was inaccurate. And this new data set will allow companies
to accurately target their efforts. It also opens up new discussions concerning the conservation,
restoration, and management of forest ecosystems.
Ecosystem conservation is a hot topic today, and this study comes in the perfect time. Along
with ecosystem conservation, recent studies have shown that deforestation has contributed to a
large amount of the global carbon emissions. Even though many companies have pledged to
stop the deforestation in order to produce goods, these policies will not succeed by 2020, which
is the goal of many of these companies (p. 3). And this study could be the key to increasing
these efforts, and helping humans reduce the growth of carbon emissions, and therefore slow
global warming.
This article does an amazing job at presenting the new data in a clear form, allowing it to be
interpreted without discrepancy. However, it should have been concise with some of the data
that the text presented. The tables and maps held all the data, and putting it within the text
lengthened the article a bit. I think that this made the article somewhat tedious in parts, and if it
was shortened, I would have had a bit less trouble reading. And finally, the first paragraph
stated that the locations of companies’ supply chains are not clear, preventing these companies
from discovering the actual source of their commodities, where they can focus their zero
deforestation efforts. The article did not follow up on this idea, as it did not provide a potential
solution. If the authors expanded and presented a resolution, it would have given me more
confidence that the deforestation prevention could be improved using this data.
I thought that Michael did a very good job presenting the data in a concise, easily understandable way which allows for easy comprehension for the reader. I also enjoyed the way he gives his own opinions based on the text and the information he knows. Finally, he did a very good job explaining the article's significance in our world today and how it applies to us. I thought that he could have given slightly more information on the effect of deforestation as described in the article as well as how this study will help humans reduce carbon emissions in practice, as this claim was not entirely supported by evidence or examples. I thought one fascinating thing was the fact that a computer algorithm has been developed explicitly for learning more about the problem of deforestation.
ReplyDeleteCharlotte Cagliostro
ReplyDeleteMr. Ippolito
AP Biology
9/21/18
Michael’s review of “Classifying Drivers of Global Forest Loss” was well written and quite informative. One aspect of his review that I appreciated was the sophistication of his writing. He was able to take a very long, complex article and write a concise and educational review. Another part of his review that I liked was the large amount of evidence Michael cited from the original article. Instead of offering the reader a more simple summary, Michael strengthened his review by adding many quotes and pieces of evidence, which gave me a better idea of the article’s main idea. The final aspect of his review that I enjoyed was his final paragraph. He provided an extremely well-thought-out critique of the article, which I appreciated.
Although there were many exceptional aspects of Michael’s review, I believe that two small areas of his piece could be improved upon. First, I would have preferred it if his review was formatted correctly; it was a bit challenging or rather annoying to deal with the irregular line breaks. If Michael were to make that simple formatting change, I believe that the review would appear more polished. My second suggestion for Michael is to add some more detail to his second paragraph, the one regarding who the loss the forestation would affect and how. I was disappointed when I didn’t see anything about the effects on humans or animals because I was curious about it.
The most interesting thing I learned from reading this review is that scientists use datasets developed through Google Earth to track deforestation. Before reading Michael's piece, I would never have thought that Google Earth could play such an important role in the surveillance of deforestation.
Anton Tarazi
ReplyDeleteCurrent Events 2
Oliveira, Sara. “Here's How We're Growing Meat in Labs Instead of in Animals.” Massive, 19 Sept. 2018, massivesci.com/articles/what-is-cultured-meat/.
Eva chose an interesting article whose subject has a fair amount of relevance to our lives in the future. A few years ago the subject of lab-grown meat would have seen like something out of a science fiction but in a few years it may be on the plates of families around the globe. In her review, Eva did a good job summarizing the topic of the article such as how she detailed between the different types of lab grown meat, structured and unstructured, and how they simulate different types of meat. Secondly, Eva also did a good job of explaining the complexity of the issue and the ramifications such as how the meat may not even be safe for human consumption. The third thing that Eva did well was that she provided a concise, logical critique of the article.
There were some things that I felt Eva left out of her review though. While she gave her opinion on what the author could have done better, I found that it was very brief and she could have added more detail to her second paragraph. Secondly, Eva did not mention her personal opinion or thoughts on the topic itself, instead summarizing what the article said. By addressing these two topics, Eva could make her review more complete and better encompass the subject.
What I find so shocking about lab-grown meat is that it may be easily accessible for us within a decade. This raises the question will I want to eat it? I do not know how others will feel but the idea of eating lab-grown meat personally disgusts me as it seems way too artificial. I chose this article because the topic is so relevant, not some obscure discovery in a lab, but rather one that may impact humanity’s diets forever. Soon people around the world will ask themselves if they want to eat this new, artificial food source.
Anna Normand
ReplyDeleteAP Biology
Mr. Ippolito
21 September 2018
I thought Michael’s review of this article was incredibly thorough and well-written. One aspect of his review that I appreciated was the fact that he referenced tables and charts from the article and incorporated relevant evidence which allowed for further comprehension of the subject. Another aspect of the review I enjoyed was his connection to relevant debates about deforestation today, which tied the article in with broader debates and schools of thought. Finally, I appreciated that his review was well-written and simplified the article without sacrificing important parts of it.
One aspect of Michael’s review that I found confusing was his assertion that this study was more accurate than others performed on the same topic. I think it would have helped his argument had he expanded on the ways in which the study provided a more accurate view of deforestation. I also would have enjoyed it if he had provided more ties to humans and our specific effects on the environment, as well as an overview of the potential risks of deforestation which might provide more context for the article.
One thing which I found incredibly interesting in the article was the fact that a computer algorithm was created to classify factors leading to deforestation. I thought this was both an incredible scientific tool and an amazing innovation which I would not have thought was possible before reading this article.