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# Mentors | ||
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Mentors are **experienced scientists who are interested in supporting a group throughout the development of their research project** between October 2024 and March 2025 nd will be compensated for their time and effort. | ||
Mentors are **experienced scientists who are interested in supporting a group throughout the development of their research project** between October 2024 and March 2025 and will be compensated for their time and effort. | ||
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## Why be a mentor? | ||
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## Eligibility criteria | ||
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1. **Educational and Professional Background:** Hold a PhD in a relevant field such as Neuroscience, Deep Learning, NeuroAI, or cliamte science, or possess equivalent experience gained through industry or other professional settings that demonstrate expertise in these areas. | ||
1. **Educational and Professional Background:** Hold a PhD in a relevant field such as Neuroscience, Deep Learning, NeuroAI, or climate science, or possess equivalent experience gained through industry or other professional settings that demonstrate expertise in these areas. | ||
2. **Project Fit:** Proficient in Python with experience conducting research related to the datasets or scientific questions of the scholars' group. A project gallery will be shared here soon. | ||
3. **Mentoring / Teaching Experience:** Experience in mentoring or supervising junior researchers. | ||
4. **Communication Skills:** Strong communication and interpersonal skills to effectively mentor and collaborate with scholars. | ||
5. **Commitment:** Availability for the program duration (October 2024 to March 2025) and commitment to regular meetings and communication with scholars and staff. | ||
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If you have any questions regarding the mentor role please feel free to contact [email protected]. | ||
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```{note} | ||
Mentor applications will open at the end of July and will be shared on this website. | ||
``` | ||
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## **Frequently asked questions** | ||
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# Understanding Land Cover Change in a Tropical Region due to Rapid Agricultural Increase: Interactions with Environmental and Socioeconomic Factors | ||
# Exploring land cover change interactions with environmental and socioeconomic factors in a tropical region due to rapid agricultural increase | ||
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Team "Beipiaosaurus moonwalk" | ||
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**Sofia Corradi Oliveira**, **Andrés Fernando Figueroa Curo**, **Magnolia Song**, **Manojna Polisetty**, **Daniela Velásquez**, **Maryann Alessandra Alata Chambilla** | ||
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Mentor: **Oz Kira** | ||
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Reviewer: **Jorge M. Uuh Sonda** | ||
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<div style="text-align: justify"> | ||
Mato Grosso, a vital part of the Amazonian Rainforest, has experienced a considerable human impact, primarily driven by agricultural and livestock expansion. The region, which once covered almost 50% with forests, has now dwindled to approximately 35%, largely due to deforestation linked to economic growth. Our study, utilizing MODIS satellite and economic data, revealed concerning trends, including an 8% reduction in forested areas and a simultaneous 6% increase in soy-planted areas and grasslands between 2001 and 2021. Correlation analyses exposed negative associations between forested areas and both environmental (Net Primary Productivity - NPP, Land Surface Temperature - LST, albedo) and socioeconomic (Gross Domestic Product - GDP, population) variables, emphasizing a direct link between economic development and deforestation. Notably, the strong correlation between 'soy-planted area' and GDP/population highlights the significant role of agricultural expansion, often tied to deforestation, in regional economic growth. Additionally, the connection between the rise in LST and significant correlations between NPP and economic variables underscores the intricate relationship between land-use changes, environmental factors, and socio-economic development in Mato Grosso. This study can be useful for decision-makers, fostering awareness and guiding the creation of a mindful approach to reduce expansive agriculture, ultimately contributing to conservation efforts in the Amazonia region. | ||
Mato Grosso, a vital part of the Amazonian Rainforest, has experienced a considerable human impact, primarily driven by agricultural expansion. The region, which once covered almost 50% with forests, has now dwindled to approximately 35%, largely due to deforestation linked to economic growth. Our study, utilizing MODIS satellite data and economic variables, revealed concerning trends, including a 7% reduction in forested areas and a simultaneous increase in croplands and grasslands between 2001 and 2021. Correlation analyses exposed negative associations between forested areas and both environmental (Net Primary Productivity - NPP, Land Surface Temperature - LST, albedo) and socioeconomic (Gross Domestic Product - GDP, population) variables, emphasizing a direct link between economic development and deforestation. Notably, the strong correlation between ‘soy-planted area’ and GDP/population highlights the significant role of agricultural expansion, often tied to deforestation, in regional economic growth. Additionally, the connection between the rise in LST and significant correlations between NPP and economic variables underscores the intricate relationship between land cover changes, environmental factors, and socio-economic development in Mato Grosso. This study can be useful for decision-makers, fostering awareness and guiding the creation of a mindful approach to reduce expansive agriculture, ultimately contributing to conservation efforts in the Amazonia region. | ||
</div> | ||
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The full micropublication will be shared here at the end of March 2024. | ||
For the full micropublication: | ||
https://doi.org/10.5281/zenodo.11002004 | ||
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For the presentation on **Exploring land cover change interactions with environmental and socioeconomic factors in a tropical region due to rapid agricultural increase:** | ||
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[![Presentation image](https://img.youtube.com/vi/Mjw4j0LdTps/0.jpg)](https://www.youtube.com/watch?v=Mjw4j0LdTps) |
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# Assessing Spatio-Temporal Precipitation Variability and Extreme Events in India | ||
# Assessing spatio-temporal precipitation variability and extreme events in India | ||
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Team "Monsoon Blues" | ||
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**Stefy Thomas**, **Khushi Dani**, **Sattiki Ganguly**, **Pandurang Choudhari** | ||
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Mentor: **Risa Madoff** | ||
With contributions from **Sintayehu Fetene Demessie** | ||
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Mentor and reviewer: **Risa Madoff** | ||
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<div style="text-align: justify"> | ||
The following project is a study on <b>“Assessing Spatio-Temporal Precipitation Variability and Extreme Events in India”</b> which highlights the critical need to understand fluctuations in extreme precipitation events due to anthropogenic climate change across various regions and across time within India. Through the study we aim to understand the degree and the number of extreme precipitation events. We have utilized the Mann-Kendall trend line to visualize the trends, indicating a positive trend for both spatial and temporal variability.The study informs flood risk preparation, water management, and climate policies, all of which contribute to the ongoing discussion of the effects of climate change. In conclusion, the statistical significance of our findings suggest that further research is needed that could help with developing early warning systems, infrastructure development and overall policy making to anticipate and thwart the effects of extreme precipitation. | ||
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The full micropublication will be shared here at the end of March 2024. | ||
For the full micropublication: | ||
https://doi.org/10.5281/zenodo.11077309 | ||
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For the presentation on **Assessing spatio-temporal precipitation variability and extreme events in India:** | ||
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[![Presentation image](https://img.youtube.com/vi/csPZujmCpz4/0.jpg)](https://www.youtube.com/watch?v=csPZujmCpz4) |
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