Soil quality is fundamental for ecosystem long term functionality, productivity and resilience to current climatic changes. Despite its importance, soil is lost and degraded at dramatic rates worldwide. In Europe, the Mediterranean areas are a hotspot for soil erosion and land degradation due to a combination of climatic conditions, soils, geomorphology and anthropic pressure. Soil organic carbon (SOC) is considered a key indicator of soil quality as it relates to other fundamental soil functions supporting crucial ecosystem services. In the present study, the functional relationships among SOC and other important soil properties were investigated in the topsoil of 38 sites under different land cover and management, distributed over three Mediterranean regions under strong desertification risk, with the final aim to define critical SOC ranges for fast loss of important soil functionalities. The study sites belonged to private and public landowners seeking to adopt sustainable land management practices to support ecosystem sustainability and productivity of their land. Data showed a very clear relationship between SOC concentrations and the other analyzed soil properties: total nitrogen, bulk density, cation exchange capacity, available water capacity, microbial biomass, C fractions associated to particulate organic matter and to the mineral soil component and indirectly with net N mineralization. Below 20 g SOC kg-1, additional changes of SOC concentrations resulted in a steep variation of all the analyzed soil indicators, an order of magnitude higher than the changes occurring between 50 and 100 g SOC kg-1 and 3-4 times the changes observed at 20-50 g SOC kg-1. About half of the study sites showed average SOC concentration of the topsoil centimetres <20 g SOC kg-1. For these areas the level of SOC might hence be considered critical and immediate and effective recovery management plans are needed to avoid complete land degradation in the next future.

The purpose of this work is to investigate trends in annual and monthly precipitation in mainland Portugal by studying long time series. The data are from ten measuring stations scattered over mainland Portugal; some of the time series date back from the 19th century. Trends in these precipitation series were examined using the Mann-Kendall non-parametric trend test and the Sen's non-parametric method. Both full monotonic trends (i.e., over the record period) and partial trends were investigated. Results provide no evidences for rejecting the null hypothesis of no trend in annual precipitation, when a monotonic linear model was used. On the other hand, the analyses of partial trends in the time series identified a sequence of alternating decreasing and increasing trends in annual precipitation, which are sometimes statistically significant. This type of behaviour was also observed for the monthly precipitation.

Planning the adaptation of agriculture and forestry landscapes to climate change remains challenging due to the need for integrating substantial amounts of information. This information ranges from climate scenarios, geographical site information, socio-economic data and several possible adaptation measures. Thus, there is an urgent need to have a framework that is capable of organizing adaptation strategies and measures in the agriculture and forestry sectors in Mediterranean climatic regions. Additionally, this framework should provide a cause effect relation with climate vulnerability to adequately support the development of adaptation planning at municipal and local (farm) level. In this context, we propose to test and evaluate a framework for climate adaptation of the agriculture and forestry sectors, based on the local causal-effect relation between adaptation strategies and measures and the level of vulnerability reduction achieved for Mediterranean areas. The framework was developed based on the combination of the DPSIR (Driving forces, Pressures, State, Impacts, Responses) and Vulnerability frameworks and reviewed 162 practical adaptation measures, further organized into strategies, complemented by a set of efficacy indicators. The framework was tested with 70 stakeholders in six stakeholder workshops for the planning of two farms and one municipal climate adaptation study, that are now in actual implementation and monitoring. The framework is composed by a set of eight adaptation strategies in which adaptation measures are clustered and assessed using efficacy indicators. In the evaluation of the adaptation framework, 96% of stakeholders considered its content as good or very good and 89% considered the final outcomes as good or very good. Finally, the framework was also used to assess and compare the adaptation strategies and measures presented in the climate adaptation plans of the three case studies. On average, 52.2% of the adaptation measures selected by the three case studies are dedicated to Ecosystem Resilience, 30.9% to Adaptive Capacity, 9.1% to Microclimates, 7.4% to Protection, and 0.3% to Mitigation strategies. This framework was considered effective in supporting adaptation planning at farm and municipal levels and useful to assess and compare adaptation plans in the frame of vulnerability reduction. Future studies can further contribute to support adaptation planning in these sectors by using, developing and streamlining this framework to additional and different socio-ecological contexts.

Climate change is expected to have a major impact on the world's environment, economy and society, especially in African countries such as Angola due to the dependence of many vital sectors on climate variability (e.g. agriculture) and their low adaptive capacity. With the advances in the availability of climate model data sets provided by programs such as the CORDEX, Angola can benefit from studies on future climate change using high‐spatial‐resolution data, which have previously been absent for this region. The purpose of this study is to analyse the projected changes in temperature and precipitation over Angola during the 21st century based on four regional climate models (RCMs). The spatial and temporal changes were analysed using a high‐ and medium‐low radiative forcing scenario to consider the uncertainty in greenhouse gas emissions. Changes in the average annual precipitation, average annual temperature and a drought index are studied for short‐, mid‐ and long‐term projections. Compared to the reference period, relevant changes are projected in temperature and precipitation indices for the different models under both emission scenarios. These changes include an increase in both the maximum and minimum temperature of up to 4.9 °C by the end of the century and an intensification of droughts. The precipitation projections are highly variable – increasing and decreasing – across the region and dependent on the RCMs. Despite these differences, the precipitation generally decreases over time (approximately −2% by 2100), with the southern region experiencing a stronger decrease in precipitation. Further investigation is needed to minimize projections uncertain, as the annual mean precipitation was overestimated by three of the RCMs (especially in the northern coastal units). Overall, these projected changes in climate can have important implications for the future of Angola, because they are expected to magnify existing problems, thus creating new risks for human and natural systems.

This work investigates recent changes in precipitation patterns manifested in long annual and monthly precipitation time series recorded in Portugal. The dataset comprises records from 14 meteorological stations scattered over mainland Portugal and the Portuguese North Atlantic Islands of Madeira and Azores; some of the time series date back to the 19th century. The data were tested for trends using the Mann-Kendall non-parametric test and Sen's non-parametric method, searching both for full monotonic trends over the record period and for partial trends. Results provide no evidence for rejecting the null hypothesis of no trend in annual precipitation, when a monotonic linear model was used. Nevertheless, the analyses of 50 years' moving averages showed an increase over time, in the recent past, for many of the series in mainland Portugal and the Islands. For the longest time series this behaviour was preceded by a decrease over time. The analyses of partial trends in the time series suggested a sequence of alternately decreasing and increasing trends in annual and monthly precipitation, which are sometimes statistically significant. The trend changing points were identified.