CHIRADZULU, Malawi — Diana Sitima’s farm on the outskirts of Malawi’s commercial capital, Blantyre, is both example and an exception. Where neighboring farmers have planted mostly maize for food and for sale in nearby markets, people drive out to buy sweet potato, pigeon peas and vegetables, bananas and avocado, and eggs produced on Sitima’s 3.5-hectare (8.6-acre) property. Sitima started farming in 1993. Unlike her neighbors, farming was a side hustle to begin with: she worked as an office assistant in Blantyre and her husband had a good job with a bank. Over the next seven years, she and her husband took out a series of micro-loans, renting small parcels of land and hiring people from the village to grow tomatoes for sale in the city. Sitima’s efforts went well, and because her family did not have to rely on their harvest for food or an income at that time, she was able to save the money she earned to take a next step. She quit her office job and acquired a farm of her own in Chiradzulu district, 15 kilometers (9 miles) east of the city. “That’s how I made money to be able to buy this land when it was put up for sale in 2006,” she says. While she was still a part-time farmer, Sitima attended several workshops, where she picked up ideas about agroecological farming — an approach combining crops, agroforestry, fish ponds, poultry and livestock, in a self-reinforcing system that protects soil health and reduces the…This article was originally published on Mongabay

The 2026 Bundibugyo Ebola outbreak in Central and East Africa has already left at least 49 people dead, with health authorities racing to stop the spread of the disease. What if they could have known ahead of time where it would begin? That’s the question behind a study published last year by Carson Telford and a group of researchers with the U.S. Centers for Disease Control (CDC). They wanted to know whether it would be possible to predict where Ebola outbreaks might start by looking at the characteristics of areas where the virus had already “spilled over” from an animal host into a human. Telford and his colleagues analyzed 24 outbreaks between 2001 and 2022, using variables like population density and forest cover to train their model. When they ran the analysis of where those outbreaks occurred, they found a high correlation with forest loss and fragmentation. The model they built with that data was strikingly accurate. It put a town in the Democratic Republic of Congo in its top 0.1% of risk areas — just a few months before an outbreak happened there in 2022. Another that followed in Uganda was in a district it had identified as being in the top 6% for that country. Mongabay’s Ashoka Mukpo spoke to Telford about the link between Ebola and deforestation, and how understanding it could help stop outbreaks early on. Medical staff carry an Ebola patient to a treatment center. Image by Moses Sawasawa via Associated Press. Mongabay: How would…This article was originally published on Mongabay