How temperate forests will respond to climate change is uncertain; projections range from severe decline to increased growth. We conducted field tests of sessile oak (Quercus petraea), a widespread keystone European forest tree species, including more than 150 000 trees sourced from 116 geographically diverse populations. The tests were planted on 23 field sites in six European countries, in order to expose them to a wide range of climates, including sites reflecting future warmer and drier climates. By assessing tree height and survival, our objectives were twofold: (i) to identify the source of differential population responses to climate (genetic differentiation due to past divergent climatic selection vs. plastic responses to ongoing climate change) and (ii) to explore which climatic variables (temperature or precipitation) trigger the population responses. Tree growth and survival were modeled for contemporary climate and then projected using data from four regional climate models for years 2071-2100, using two greenhouse gas concentration trajectory scenarios each. Overall, results indicated a moderate response of tree height and survival to climate variation, with changes in dryness (either annual or during the growing season) explaining the major part of the response. While, on average, populations exhibited local adaptation, there was significant clinal population differentiation for height growth with winter temperature at the site of origin. The most moderate climate model (HIRHAM5-EC; rcp4.5) predicted minor decreases in height and survival, while the most extreme model (CCLM4-GEM2-ES; rcp8.5) predicted large decreases in survival and growth for southern and southeastern edge populations (Hungary and Turkey). Other nonmarginal populations with continental climates were predicted to be severely and negatively affected (Bercé, France), while populations at the contemporary northern limit (colder and humid maritime regions; Denmark and Norway) will probably not show large changes in growth and survival in response to climate change.
Cites: Nature. 2009 Dec 24;462(7276):1052-520033047
There is a strong connection between economic growth and development of cities. Economic growth tends to stimulate city growth, and city economies have often shaped innovative environments that in turn support economic growth. Simultaneously, social and environmental problems related to city growth can be serious threats to the realization of the socio-economic contributions that cities can make. However, as a result of considerable diversity of competences combined with interactive learning and innovation, cities may also solve these problems. The 'urban order' may form a platform for innovative problem solving and potential spill-over effects, which may stimulate further economic growth and development. This paper discusses how waste problems of cities can be transformed to become part of new, more sustainable solutions. Two cases are explored: Aalborg in Denmark and Malm? in Sweden. It is shown that the cities have the potential to significantly contribute to a more sustainable development through increased material recycling and energy recovery. Waste prevention may increase this potential. For example, instead of constituting 3% of the total greenhouse gas emission problem, it seems possible for modern European cities to contribute to greenhouse gas emission reduction by 15% through up to date technology and integrated waste management systems for material and energy recovery. Going from being part of the problem to providing solutions; however, is not an easy endeavour. It requires political will and leadership, supportive regulatory frameworks, realistic timetables/roadmaps, and a diverse set of stakeholders that can provide the right creative and innovative mix to make it possible.
We examine how core professional and institutional actors in the innovation system conceptualize climate change adaptation in regards to pluvial flooding-and how this influences innovation. We do this through a qualitative case study in Copenhagen with interconnected research rounds, including 32 semi-structured interviews, to strengthen the interpretation and analysis of qualitative data. We find that the term "climate change adaptation" currently has no clearly agreed definition in Copenhagen; instead, different actors use different conceptualizations of climate change adaptation according to the characteristics of their specific innovation and implementation projects. However, there is convergence among actors towards a new cognitive paradigm, whereby economic goals and multifunctionality are linked with cost-benefit analyses for adapting to extreme rain events on a surface water catchment scale. Differences in definitions can lead to both successful innovation and to conflict, and thus they affect the city's capacity for change. Our empirical work suggests that climate change adaptation can be characterized according to three attributes: event magnitudes (everyday, design, and extreme), spatial scales (small/local, medium/urban, and large/national-international), and (a wide range of) goals, thereby resulting in different technology choices.
Complex ecological models are used to predict the consequences of anticipated future changes in climate and nutrient loading for lake water quality. These models may, however, suffer from nonuniqueness in that various sets of model parameter values may yield equally satisfactory representations of the system being modeled, but when applied in future scenarios these sets of values may divert considerably in their simulated outcomes. Compilation of an ensemble of model runs allows us to account for simulation variability arising from model parameter estimates. Thus, we propose a new approach for aquatic ecological models creating a more robust prediction of future water quality. We used our ensemble approach in an application of the widely used PCLake model for Danish shallow Lake Arreskov, which during the past two decades has demonstrated frequent shifts between turbid and clear water states. Despite marked variability, the span of our ensemble runs encapsulated 70–90% of the observed variation in lake water quality. The model exercise demonstrates that future warming and increased nutrient loading lead to lower probability of a clear water, vegetation-rich state and greater likelihood of cyanobacteria dominance. In a 6.0°C warming scenario, for instance, the current nutrient loading of nitrogen and phosphorus must be reduced by about 75% to maintain the present ecological state of Lake Arreskov, but even in a near-future 2.0°C warming scenario, a higher probability of a turbid, cyanobacteria-dominated state is predicted. As managers may wish to determine the probability of achieving a certain ecological state, our proposed ensemble approach facilitates new ways of communicating future stressor impacts.
Fresh waters make a disproportionately large contribution to greenhouse gas (GHG) emissions, with shallow lakes being particular hot spots. Given their global prevalence, how GHG fluxes from shallow lakes are altered by climate change may have profound implications for the global carbon cycle. Empirical evidence for the temperature dependence of the processes controlling GHG production in natural systems is largely based on the correlation between seasonal temperature variation and seasonal change in GHG fluxes. However, ecosystem-level GHG fluxes could be influenced by factors, which while varying seasonally with temperature are actually either indirectly related (e.g. primary producer biomass) or largely unrelated to temperature, for instance nutrient loading. Here, we present results from the longest running shallow-lake mesocosm experiment which demonstrate that nutrient concentrations override temperature as a control of both the total and individual GHG flux. Furthermore, testing for temperature treatment effects at low and high nutrient levels separately showed only one, rather weak, positive effect of temperature (CH4 flux at high nutrients). In contrast, at low nutrients, the CO2 efflux was lower in the elevated temperature treatments, with no significant effect on CH4 or N2 O fluxes. Further analysis identified possible indirect effects of temperature treatment. For example, at low nutrient levels, increased macrophyte abundance was associated with significantly reduced fluxes of both CH4 and CO2 for both total annual flux and monthly observation data. As macrophyte abundance was positively related to temperature treatment, this suggests the possibility of indirect temperature effects, via macrophyte abundance, on CH4 and CO2 flux. These findings indicate that fluxes of GHGs from shallow lakes may be controlled more by factors indirectly related to temperature, in this case nutrient concentration and the abundance of primary producers. Thus, at ecosystem scale, response to climate change may not follow predictions based on the temperature dependence of metabolic processes.