Tobias Lung

Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest

Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.

Climate change and the emergence of vector-borne diseases in Europe: case study of dengue fever.

BackgroundDengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios.MethodsWe used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985–2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961–1990) and three climate change scenarios: short-term 2011–2040, medium-term 2041–2070 and long-term 2071–2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10xa0km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence.ResultsThe results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy.ConclusionsThis risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world.

A comparative assessment of land cover dynamics of three protected forest areas in tropical eastern Africa

Processes of deforestation, known to threaten tropical forest biodiversity, have not yet been studied sufficiently in East Africa. To shed light on the patterns and causes of human influences on protected forest ecosystems, comparisons of different study areas regarding land cover dynamics and potential drivers are needed. We analyze the development of land cover since the early 1970s for three protected East African rainforests and their surrounding farmlands and assess the relationship between the observed changes in the context of the protection status of the forests. Processing of Landsat satellite imagery of eight or seven time steps in regular intervals results in 12 land cover classes for the Kakamega–Nandi forests (Kenya) and Budongo Forest (Uganda) whereas ten are distinguished for Mabira Forest (Uganda). The overall classification accuracy assessed for the yearxa02001 or 2003 is similarly high for all three study areas (81% to 85%). The time series reveal that, despite their protection status, Kakamega–Nandi forests and Mabira Forest experienced major forest decrease, the first a continuous forest loss of 31% between 1972/1973 and 2001, the latter an abrupt loss of 24% in the late 1970s/early 1980s. For both forests, the temporally dense time series show short-term fluctuations in forest classes (e.g., areas of forest regrowth since the 1980s or exotic secondary bushland species from the 1990s onwards). Although selectively logged, Budongo Forest shows a much more stable forest cover extent. A visual overlay with population distribution for all three regions clearly indicates a relationship between forest loss and areas of high population density, suggesting population pressure as a main driver of deforestation. The revealed forest losses due to local and commercial exploitation further demonstrate that weak management impedes effective forest protection in East Africa.

Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators

Despite an increasing understanding of potential climate change impacts in Europe, the associated uncertainties remain a key challenge. In many impact studies, the assessment of uncertainties is underemphasised, or is not performed quantitatively. A key source of uncertainty is the variability of climate change projections across different regional climate models (RCMs) forced by different global circulation models (GCMs). This study builds upon an indicator-based NUTS-2 level assessment that quantified potential changes for three climate-related hazards: heat stress, river flood risk, and forest fire risk, based on five GCM/RCM combinations, and non-climatic factors. First, a sensitivity analysis is performed to determine the fractional contribution of each single input factor to the spatial variance of the hazard indicators, followed by an evaluation of uncertainties in terms of spread in hazard indicator values due to inter-model climate variability, with respect to (changes in) impacts for the period 2041–70. The results show that different GCM/RCM combinations lead to substantially varying impact indicators across all three hazards. Furthermore, a strong influence of inter-model variability on the spatial patterns of uncertainties is revealed. For instance, for river flood risk, uncertainties appear to be particularly high in the Mediterranean, whereas model agreement is higher for central Europe. The findings allow for a hazard-specific identification of areas with low vs. high model agreement (and thus confidence of projected impacts) within Europe, which is of key importance for decision makers when prioritising adaptation options.

Combining long-term land cover time series and field observations for spatially explicit predictions on changes in tropical forest biodiversity

Combining spatially explicit land cover data from remote-sensing and faunal data from field observations is increasingly applied for landscape-scale habitat and biodiversity assessments, but without modelling changes quantitatively over time. In a novel approach, we used a long-term time series including historical map data to predict the influence of one century of tropical forest change on keystone species or indicator groups in the Kakamega–Nandi forests, western Kenya. Four time steps of land cover data between 1912/13 and 2003, derived from Landsat satellite imagery, aerial photography and old topographic maps, formed the basis for extrapolating species abundance data on the army ant Dorylus wilverthi, the guild of ant-following birds and three habitat guilds of birds differing in forest dependency. To predict the species spatio-temporal distribution, we combined spatially explicit geographical information system (GIS)-based modelling with statistical modelling, that is, ordinary least square (OLS) regression models for D. wilverthi and simultaneous autoregressive (SAR) models for ant-following birds. We directly related bird habitat guilds to five forest classes as distinguished in the land cover time series. Extrapolation results over time predict dramatic losses in abundance for D. wilverthi (56%), ant-following birds (58%) and forest bird individuals in general (47%) due to a forest loss of 31% and small-scale fragmentation within the past century. Extrapolations based on a scenario of further deforestation revealed the negative consequences of clearing and splitting up continuous forest into isolated patches, whereas a reforestation scenario suggests the positive impact of natural forest regrowth and indigenous-tree planting. This study demonstrates the high potential of integrating remotesensing and field-based faunal data for landscape-scale quantitative assessments over time. In addition, it shows the suitability of extrapolation studies for evaluating measures of forest conservation.

Mainstreaming climate change in regional development policy in Europe: five insights from the 2007–2013 programming period

The EU Structural and Cohesion Funds (SCF) are potentially important instruments for supporting climate policy-related efforts and addressing unevenly distributed capacities for successful mitigation and adaptation across the EU. This paper reports on the level of climate mainstreaming in EU regional development policy in the 2007–2013 programming period: first, we explore the normative commitment to climate change concerns through an analysis of the National Strategic Reference Frameworks (NSRFs) in which all 27 Member States specify their development and funding priorities. Second, we analyze the substantive commitments by mapping financial allocations from the SCF related to climate mitigation and adaptation. Based on this, we gain five main insights, which are relevant to future mainstreaming efforts and which may have important implications for the wider debate on the purpose of European regional policy: (1) mitigation appears well mainstreamed in EU cohesion policies, both in normative and financial terms, whereas adaptation is hardly considered. (2) Rhetorical commitment to climate concerns in the strategy documents does not necessarily match financial allocations to respective priorities. (3) Neither mitigation nor adaptation-relevant priorities and allocations in the NSRFs can be linked to the ambitious mitigation targets and low adaptive capacity, respectively. (4) There is ample potential to improve climate-relevant SCF support in the area of adaptation, particularly given that several existing priority areas for funding coincide with the climate adaptation agenda. (5) By conditioning a minimum percentage of funds to be spent on priority areas (earmarking), cohesion policy also gains meaning as a burden sharing instrument for adaptation to climate change.