Global environmental changes (GEC) such as climate change (CC) and climate variability have serious impacts in the tropics, particularly in Africa. These are compounded by changes in land use/land cover, which in turn are driven mainly by economic and population growth, and urbanization. These factors create a feedback loop, which affects ecosystems and particularly ecosystem services, for example plant-insect interactions, and by consequence agricultural productivity. We studied effects of GEC at a local level, using a traditional coffee production area in greater Nairobi, Kenya. We chose coffee, the most valuable agricultural commodity worldwide, as it generates income for 100 million people, mainly in the developing world. Using the coffee berry borer, the most serious biotic threat to global coffee production, we show how environmental changes and different production systems (shaded and sun-grown coffee) can affect the crop. We combined detailed entomological assessments with historic climate records (from 1929–2011), and spatial and demographic data, to assess GEC's impact on coffee at a local scale. Additionally, we tested the utility of an adaptation strategy that is simple and easy to implement. Our results show that while interactions between CC and migration/urbanization, with its resultant landscape modifications, create a feedback loop whereby agroecosystems such as coffee are adversely affected, bio-diverse shaded coffee proved far more resilient and productive than coffee grown in monoculture, and was significantly less harmed by its insect pest. Thus, a relatively simple strategy such as shading coffee can tremendously improve resilience of agro-ecosystems, providing small-scale farmers in Africa with an easily implemented tool to safeguard their livelihoods in a changing climate.
Coastal management is criƟ cal in view of the danger posed to coastal communiƟ es by fl ooding from the sea due to storm surges, sea-level rise and Tsunamis. The low-lying Kenyan coast is vulnerable to these hazards, therefore modeling their eff ects is necessary for understanding their socioeconomic impacts. A Decision Support Tool (DST) was developed to study the hydrodynamics along the Kenyan coast. The bathymetry grid for the DST was created using Arc View GIS from nauƟ cal charts. MIKE 21 Hydrodynamic Module (HD) Demo version was used to organize the bathymetry and enforce boundary condiƟ ons for ELCOM simulaƟ on. Tidal data was obtained from both the Kenya Meteorological Department's Ɵ dal gauges and the GLOSS staƟ on. The computed Ɵ de and currents from ELCOM were validated using graphical and staƟ sƟ cal comparison. Their predicƟ ve ability was analyzed. The ELCOM water levels and currents compared well to observed values, and their dominant signals were detectable. ELCOM could, therefore, simulate and forecast coastal hydrodynamics. This DST can assist the Government in operaƟ onal forecasƟ ng for marine environmental protecƟ on, resources management and disaster risk reducƟ on and miƟ gaƟ on as well as infrastructure mapping and development along the Kenyan coast.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.