Das Projekt "Towards a Guideline for Digital Soil Mapping in Ecuador" wird vom Umweltbundesamt gefördert und von Universität Bayreuth, Abteilung Bodenphysik durchgeführt. Research experience in digital soil mapping (DSM) shall be extended and deepened in two further research areas in order to develop a guideline for DSM in Ecuador. The guideline will give an overview: a) about the DSM approach, b) the different sampling designs developed according to the area size, accessibility and terrain complexity, c) the various methods from the field of supervised machine learning to develop digital soil maps, and d) the implementation with open source software. The soil-landscapes of the three investigation areas will be analysed and soil-landscape models will be developed by supervised machine learning techniques, in order to spatially predict soil properties from point data based on environmental prediction parameters. By using the so developed digital soil maps as principal input, a functional soil-landscape analysis is carried out to determine landslide, erosion and anthropogenic disturbance risk zones as well as estimate the soil organic carbon stocks and soil fertility.
Das Projekt "Quantification of functional hydro-biogeochemical indicators in Ecuadorian ecosystems and their reaction on global change" wird vom Umweltbundesamt gefördert und von Universität Gießen, Institut für Landschaftsökologie und Ressourcenmanagement, Professur für Landschafts-, Wasser- und Stoffhaushalt durchgeführt. Water is an intrinsic component of ecosystems acting as a key agent of lateral transport for particulate and dissolved nutrients, forcing energy transfers, triggering erosion, and driving biodiversity patterns. Given the drastic impact of land use and climate change on any of these components and the vulnerability of Ecuadorian ecosystems with regard to this global change, indicators are required that not merely describe the structural condition of ecosystems, but rather capture the functional relations and processes. This project aims at investigating a set of such functional indicators from the fields of hydrology and biogeochemistry. In particular we will investigate (1) flow regime and timing, (2) nutrient cycling and flux rates, and (3) sediment fluxes as likely indicators. For assessing flow regime and timing we will concentrate on studying stable water isotopes to estimate mean transit time distributions that are likely to be impacted by changes in rainfall patterns and land use. Hysteresis loops of nitrate concentrations and calculated flux rates will be used as functional indicators for nutrient fluxes, most likely to be altered by changes in temperature as well as by land use and management. Finally, sediment fluxes will be measured to indicate surface runoff contribution to total discharge, mainly influenced by intensity of rainfall as well as land use. Monitoring of (1) will be based on intensive sampling campaigns of stable water isotopes in stream water and precipitation, while for (2) and (3) we plan to install automatic, high temporal-resolution field analytical instruments. Based on the data obtained by this intensive, bust cost effective monitoring, we will develop the functional indicators. This also provides a solid database for process-based model development. Models that are able to simulate these indicators are needed to enable projections into the future and to investigate the resilience of Ecuadorian landscape to global change. For the intended model set up we will couple the Catchment Modeling Framework, the biogeochemical LandscapeDNDC model and semi-empirical models for aquatic diversity. Global change scenarios will then be analyzed to capture the likely reaction of functional indicators. Finally, we will contribute to the written guidelines for developing a comprehensive monitoring program for biodiversity and ecosystem functions. Right from the beginning we will cooperate with four SENESCYT companion projects and three local non-university partners to ensure that the developed monitoring program will be appreciated by locals and stakeholders. Monitoring and modelling will focus on all three research areas in the Páramo (Cajas National Park), the dry forest (Reserva Laipuna) and the tropical montane cloud forest (Reserva Biologica San Francisco).