Livia Rasche

Key factors affecting the future provision of tree-based forest ecosystem goods and services

The continuous provisioning of forest ecosystem goods and services (EGS) is of considerable interest to society. To provide insights on how much EGS provision will change with a changing climate and which factors will influence this change the most, we simulated forest stands on six climatically different sites in Central Europe under several scenarios of species diversity, management, and climate change. We evaluated the influence of these factors on the provision of a range of tree-based EGS, represented by harvested basal area, total biomass, stand diversity, and productivity. The most influential factor was species diversity, with diverse forest stands showing a lower sensitivity to climate change than monocultures. Management mainly influenced biomass, with the most intensively managed stands retaining more of their original biomass than others. All three climate-change scenarios yielded very similar results. We showed that (1) only few factor combinations perform worse under climate-change conditions than others, (2) diversity aspects are important for adaptive management measures, but for some indicators, management may be more important than diversity, and (3) at locations subject to increasing drought, the future provision of EGS may decrease regardless of the factor combination. This quantitative evaluation of the influence of different factors on changes in the provision of forest EGS with climate change represents an important step towards the design of more focused adaptation strategies and highlights key factors that should be considered in simulation studies under climate change.

Increasing social welfare by taxing pesticide externalities in the Indian cotton sector

BACKGROUND Pesticide use in the Indian cotton industry has decreased with the introduction of Bt cotton, but rates are still high in comparison with other countries. The adoption of alternative strategies, such as integrated pest management, has been slow, even though benefits are potentially high, more so if the full costs of the external effects of the technologies are taken into account. In order to estimate true societal benefits of different strategies, we compare their external costs and economic performance under external cost taxation, using a state-of-the-art partial equilibrium model of the Indian agricultural sector. RESULTS Pesticide externalities lower social welfare in the Indian cotton sector by

The importance of climate variability changes for future levels of tree-based forest ecosystem services

US 400-2200 million, depending on the technologies employed. A full internalisation reduces producer revenues by

Modeling land suitability for Coffea arabica L. in Central America

US 100 ha-1 if only Bt cotton is used, and by

Benefits of Coordinated Water Resource System Planning in the Cauca-Magdalena River Basin

US 30 ha-1 if IPM is another option. Consumers do not start to lose surplus until 20-70% are internalised, and losses are smaller if all technologies are available. CONCLUSION External pesticide costs can be internalised partially without substantially affecting consumer surplus while still increasing social welfare, but producers need to have access to and the knowledge to employ all available cotton production technologies to minimise losses.

A 2 °C warmer world is not safe for ecosystem services in the European Alps

The climate is changing, yet to which degree and in what pattern remains uncertain in many areas. In forest science, mainly impacts of long-term mean changes in temperature and precipitation distributions are studied. This paper therefore presents a sensitivity analysis to determine the importance of accounting for variability changes. A 10*10 matrix of different mean annual temperatures and precipitation sums is set up, covering the temperate forest zone of Europe, and the current level of several ecosystem services (ES) is calculated. Subsequently, mean and variability of temperature and precipitation distributions are changed in different steps, and new ES levels calculated. The results show that for the study of climate change impacts on forest ES, climate parameter variability is of secondary importance. The trends are well represented with scenarios of mean climate parameter changes only; however, on moisture-limited and heat-stressed sites impacts of changes in variability gain in importance. Most of these impacts are negative, and can be observed not only in monocultures already at their physiological limit, but also in diverse stands. Different ES, however, show different sensitivities towards changes in mean and variability, underlining the need to develop adaptation measures tailored to the sites and ES of interest.

Enhancing gap model accuracy by modeling dynamic height growth and dynamic maximum tree height

Abstract Agricultural planning processes at farm to national level are essential for assessing and reacting to land conditions, opportunities, and threats for coffee production. However, lack or uncertainty of information is common during these processes. Bayesian networks can be used to manage these uncertainties. We, therefore, developed the first Bayesian network model for an Agroecological Land Evaluation for Coffea arabica L. (ALECA). A newly developed set of suitability functions was used to populate the nodes in the network. ALECA was then adjusted and validated to Central America. The results show that even without the use of coffee maps as input, ALECA accurately scores the suitability of actual coffee areas for coffee production as higher than that non-coffee areas, and can accurately predict the known order of quality of coffee reference zones in Central America. The results also show that ALECA can be used as a decision-support tool even under data uncertainty.

Getting a virtual forester fit for the challenge of climatic change

The Magdalena watershed in Colombia is the most densely populated and economically important region in the country. While Colombia is generally classified as a water-rich country, it is expected that water shortages will occur in the future without adequate planning and investments in water management infrastructures. Currently, even though all instruments required for an integrated water resource management are present in Colombia, they are employed independently from each other and thus not very efficient. To estimate the potential benefits of a more coordinated water management planning, especially in consideration of projected changes in water availability and demand in the near future, we developed a constrained welfare maximization model of the watershed (CAMARI). We ran the model with three different scenarios of future water availability, based on RCPs 2.6, 4.5 and 6.0, and with two planning modes: coordinated and uncoordinated. The results show that a coordinated planning of investments in water management infrastructures increases welfare by 2–18% over the next century in the Magdalena river basin, which corresponds to average annual savings from US

Potential effects of perfect seasonal climate forecasting on agricultural markets, welfare and land use: A case study of Spain

610 million to US

A generic pest submodel for use in integrated assessment models

6.4 billion. Benefits increase as water availability decreases. Our results also show that water demand from the agricultural sector is projected to rise in future, which further underlines the necessity for robust governance mechanisms to keep conflicts between sectors to a minimum.