Interactive Discussion

From Allison Pecenka on Collaboration and Partnership

I really enjoyed the Science Panel for the Amazon reading and felt that a comprehensive report to this extent marks a very powerful step towards international conservation efforts coming to fruition. First of all, I found the website interface to be extremely well-designed and believe it did a great job of capturing and maintaining the viewer’s attention through shocking statistics, dynamic graphics and the interactive scrolling feature. As far as the report itself, I agreed with its structuring of content into 4 parts and thought this presented the data in its most intuitive and comprehensible format. The selection of scientists from Amazonian countries was another great component of the report, underscoring the necessity of local perspectives in the assessment of these regions and planning of measures to conserve them. I found point BKG 7.2 (pg. 21) very interesting in its explanation of the new “global development paradigm” emerging based on neoliberal concepts and pushing Latin America towards a more market-oriented economy. This point provided a more complete explanation for me on how exactly public lands were transformed into private holdings and when rapid urbanization started occurring in the region. I also really appreciated Figure 10 (pg. 29) on drivers of change leading to tipping points in Amazonian rainforests and believe its information can be integrated into our GIA Theory of Change model. I believe feedback mechanisms are a key consideration in Amazonian conservation planning and could greatly benefit our work if examined further. For example, a land cover map of the Amazon with classifications of the three potential states: white-sand savanna, open-canopy degraded forest or closed-canopy degraded secondary forest, would greatly aid in conservation planning by identifying key areas of focus with the highest restoration potential, along with areas that may be too degraded to realistically restore. This led me to think about the potential usage of predictive vegetation modeling through GIS software to determine which areas of land will support the most biodiversity under climate change-related conditions, then overlaying this output with the map of land cover restoration potential to determine which areas (satisfying both conditions) should receive the greatest focus in conservation initiatives.