Direct and indirect effects of invasion by the alien tree Ailanthus altissima on riparian plant communities and ecosystem multifunctionality

Most existing studies addressing the effects of invasive species on biodiversity focus on species richness ignoring better indicators of biodiversity and better predictors of ecosystem functioning such as the diversity of evolutionary histories (phylodiversity). Moreover, no previous study has separated the direct effect of alien plants on multiple ecosystem functions simultaneously (multifunctionality) from those indirect ones mediated by the decrease on biodiversity caused by alien plants. We aimed to analyze direct and indirect effects, mediated or not by its effect on biodiversity, of the invasive tree Ailanthus altissima on ecosystem multifunctionality of riparian habitats under Mediterranean climate. We measured vegetation attributes (species richness and phylodiversity) and several surrogates of ecosystem functioning (understory plant biomass, soil enzyme activities, available phosphorous and organic matter) in plots infested by A. altissima and in control (non-invaded) ones. We used structural equation modelling to tease apart the direct and indirect effects of A. altissima on ecosystem multifunctionality. Our results suggest that lower plant species richness, phylodiversity and multifunctionality were associated to the presence of A. altissima. When analyzing each function separately, we found that biodiversity has the opposite effect of the alien plant on all the different functions measured, therefore reducing the strength of the effect (either positive or negative) of A. altissima on them. This is one of the few existing studies addressing the effect of invasive species on phylodiversity and also studying the effect of invasive species on multiple ecosystem functions simultaneously.

Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data

Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.

Developing a Framework for Stakehoder Consultation in the Umbeluzi River Basin: Project Report

A Framework for a Consultation Process: Transboundary cooperation and sustainable water management is urgently needed in the up-stream/down-stream situation of the Umbeluzi River Basin between the Kingdom of Swaziland and the Republic of Mozambique. Thus, the Joint Water Commission (JWC) of the two riparian countries initiated the Umbeluzi River Basin Initiative (URBI) with the objective to develop a joint management plan of the river basin. In response to the request by SADC as well as SDC, a collaboration within CDE’s Eastern and Southern Africa Partnership Programme ESAPP was agreed upon. The project’s general objective is to provide conceptual and methodological support in the design of a consultative process with the aim to assure the participation of all water users within the river basin.

Effects of climate, fire, and humans on forest dynamics: forest simulations compared to the palaeological record

In order to find out which factors influenced the forest dynamics in northern Italy during the Holocene, a palaeoecological approach involving pollen analysis was combined with ecosystem modelling. The dynamic and distribution based forest model DisCForm was run with different input scenarios for climate, species immigration, fire, and human impact and the similarity of the simulations with the original pollen record was assessed. From the comparisons of the model output and the pollen core, it appears that immigration was most important in the first part of the Holocene, and that fire and human activity had a major influence in the second half. Species not well represented in the simulation outputs are species with a higher abundance in the past than today (Corylus), with their habitat in riparian forests (Alnus) or with a strong response to human impact (Castanea).