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The number of people exposed to natural hazards has grown steadily over recent decades, mainly due to increasing exposure in hazard-prone areas. In the future, climate change could further enhance this trend. Still, empirical and comprehensive insights into individual recovery from natural hazards are largely lacking, hampering efforts to increase societal resilience. Drawing from a sample of 710 residents affected by flooding across Germany in June 2013, we empirically explore a wide range of variables possibly influencing self-reported recovery, including flood-event characteristics, the circumstances of the recovery process, socio-economic characteristics, and psychological factors, using multivariate statistics. We found that the amount of damage and other flood-event characteristics such as inundation depth are less important than socio-economic characteristics (e.g., sex or health status) and psychological factors (e.g., risk aversion and emotions). Our results indicate that uniform recovery efforts focusing on areas that were the most affected in terms of physical damage are insufficient to account for the heterogeneity in individual recovery results. To increase societal resilience, aid and recovery efforts should better address the long-term psychological effects of floods.
Shrinking glaciers in the Hindu Kush-Karakoram-Himalaya-Nyainqentanglha (HKKHN) region have formed several thousand moraine-dammed glacial lakes(1-3), some of these having grown rapidly in past decades(3,4). This growth may promote more frequent and potentially destructive glacial lake outburst floods (GLOFs)(5-7). Testing this hypothesis, however, is confounded by incomplete databases of the few reliable, though selective, case studies. Here we present a consistent Himalayan GLOF inventory derived automatically from all available Landsat imagery since the late 1980s. We more than double the known GLOF count and identify the southern Himalayas as a hotspot region, compared to the more rarely affected Hindu Kush-Karakoram ranges. Nevertheless, the average annual frequency of 1.3 GLOFs has no credible posterior trend despite reported increases in glacial lake areas in most of the HKKHN3,8, so that GLOF activity per unit lake area has decreased since the late 1980s. We conclude that learning more about the frequency and magnitude of outburst triggers, rather than focusing solely on rapidly growing glacial lakes, might improve the appraisal of GLOF hazards.
Intraspecific trait variability plays an important role in species adaptation to climate change. However, it still remains unclear how plants in semi-arid environments respond to increasing aridity. We investigated the intraspecific trait variability of two common Mediterranean annuals (Geropogon hybridus and Crupina crupinastrum) with similar habitat preferences. They were studied along a steep precipitation gradient in Israel similar to the maximum predicted precipitation changes in the eastern Mediterranean basin (i.e. -30% until 2100). We expected a shift from competitive ability to stress tolerance with decreasing precipitation and tested this expectation by measuring key functional traits (canopy and seed release height, specific leaf area, N-and P-leaf content, seed mass). Further, we evaluated generative bet-hedging strategies by different seed traits. Both species showed different responses along the precipitation gradient. C. crupinastrum exhibited only decreased plant height toward saridity, while G. hybridus showed strong trends of generative adaptation to aridity. Different seed trait indices suggest increased bet-hedging of G. hybridus in arid environments. However, no clear trends along the precipitation gradient were observed in leaf traits (specific leaf area and leaf N-/P-content) in both species. Moreover, variance decomposition revealed that most of the observed trait variation (>> 50%) is found within populations. The findings of our study suggest that responses to increased aridity are highly species-specific and local environmental factors may have a stronger effect on intraspecific trait variation than shifts in annual precipitation. We therefore argue that trait-based analyses should focus on precipitation gradients that are comparable to predicted precipitation changes and compare precipitation effects to effects of local environmental factors. (C) 2017 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.
The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.
Jointly with the Global North, the rise of the Global South has come at a high cost to the environment. Driven by its high energy intensity and the use of fossil fuels, the South has contributed a significant portion of global emissions during the last 30 years, and is now contributing some 63% of today's total GHG emissions (including land-use change and forestry). Similar to the Global North, the Global South's emissions are heavily concentrated: India and China alone account for some 60% and the top 10 countries for some 78% of the group's emissions, while some 120 countries account for only 22%. Without highlighting such differences, it makes little sense to use the term 'Global South'. Its members are affected differently, and contribute differently to global climate change. They neither share a common view, nor do they pursue joint interests when it comes to international climate negotiations. Instead, they are organised into more than a dozen subgroups of the global climate regime. There is no single climate strategy for the Global South, and climate action will differ enormously from country to country. Furthermore, just and equitable transitions may be particularly challenging for some countries.
Badlands have long been considered as model landscapes due to their perceived close relationship between form and process. The often intense features of erosion have also attracted many geomorphologists because the associated high rates of erosion appeared to offer the opportunity for studying surface processes and the resulting forms. Recently, the perceived simplicity of badlands has been questioned because the expected relationships between driving forces for erosion and the resulting sediment yield could not be observed. Further, a high variability in erosion and sediment yield has been observed across scales. Finally, denudation based on currently observed erosion rates would have lead to the destruction of most badlands a long time ago. While the perceived simplicity of badlands has sparked a disproportional (compared to the land surface they cover) amount of research, our increasing amount of information has not necessarily increased our understanding of badlands in equal terms. Overall, badlands appear to be more complex than initially assumed. In this paper, we review 40 years of research in the Zin Valley Badlands in Israel to reconcile some of the conflicting results observed there and develop a perspective on the function of badlands as model landscapes. While the data collected in the Zin Valley clearly confirm that spatial and temporal patterns of geomorphic processes and their interaction with topography and surface properties have to be understood, we still conclude that the process of realizing complexity in the "simple" badlands has a model function both for our understanding as well as perspective on all landscape systems.
Estimates of present and future extreme sub-hourly rainfall are derived from a daily spatial followed by a sub-daily temporal downscaling, the latter of which incorporates a novel, and crucial, temperature sensitivity. Specifically, daily global climate fields are spatially downscaled to local temperature T and precipitation P, which are then disaggregated to a temporal resolution of 10 min using a multiplicative random cascade model. The scheme is calibrated and validated with a group of 21 station records of 10-min resolution in Germany. The cascade model is used in the classical (denoted as MC) and in the new T-sensitive (MC+) version, which respects local Clausius-Clapeyron (CC) effects such as CC scaling. Extreme P is positively biased in both MC versions. Observed T sensitivity is absent in MC but well reproduced by MC+. Long-term positive trends in extreme sub-hourly P are generally more pronounced and more significant in MC+ than in MC. In units of 10-min rainfall, observed centennial trends in annual exceedance counts (EC) of P > 5 mm are +29% and in 3-yr return levels (RL) +27%. For the RCP4.5-simulated future, higher extremes are projected in both versions MC and MC+: per century, EC increases by 30% for MC and by 83% for MC+; the RL rises by 14% for MC and by 33% for MC+. Because the projected daily P trends are negligible, the sub-daily signal is mainly driven by local temperature.
Temperate forest soils of central Europe are regarded as important pools for soil organic carbon (SOC) and thought to have a high potential for carbon (C) sequestration. However, comprehensive data on total SOC storage, particularly under different forest types, and its drivers is limited. In this study, we analyzed a forest data set of 596 completely sampled soil profiles down to the parent material or to a depth of 1 m within Bavaria in southeast Germany in order to determine representative SOC stocks under different forest types in central Europe and the impact of different environmental parameters. We calculated a total median SOC stock of 9.8 kg m(-2) which is considerably lower compared with many other inventories within central Europe that used modelled instead of measured soil properties. Statistical analyses revealed climate as controlling parameter for the storage of SOC with increasing stocks in cool, humid mountainous regions and a strong decrease in areas with higher temperatures. No significant differences of total SOC storage were found between broadleaf, coniferous and mixed forests. However, coniferous forests stored around 35% of total SOC in the labile organic layer that is prone to human disturbance, forest fires and rising temperatures. In contrast, mixed and broadleaf forests stored the major part of SOC in the mineral soil. Moreover, these two forest types showed unchanged or even slightly increased mineral SOC stocks with higher temperatures, whereas SOC stocks in mineral soils under coniferous forest were distinctly lower. We conclude that mixed and broadleaf forests are more advantageous for C sequestration than coniferous forests. An intensified incorporation of broadleaf species in extent coniferous forests of Bavaria would prevent substantial SOC losses as a result of rising temperatures in the course of climate change.
The global warming potential of nitrous oxide (N2O) and its long atmospheric lifetime mean its presence in the atmosphere is of major concern, and that methods are required to measure and reduce emissions. Large spatial and temporal variations means, however, that simple extrapolation of measured data is inappropriate, and that other methods of quantification are required. Although process-based models have been developed to simulate these emissions, they often require a large amount of input data that is not available at a regional scale, making regional and global emission estimates difficult to achieve. The spatial extent of organic soils means that quantification of emissions from these soil types is also required, but will not be achievable using a process-based model that has not been developed to simulate soil water contents above field capacity or organic soils. The ECOSSE model was developed to overcome these limitations, and with a requirement for only input data that is readily available at a regional scale, it can be used to quantify regional emissions and directly inform land-use change decisions. ECOSSE includes the major processes of nitrogen (N) turnover, with material being exchanged between pools of SOM at rates modified by temperature, soil moisture, soil pH and crop cover. Evaluation of its performance at site-scale is presented to demonstrate its ability to adequately simulate soil N contents and N2O emissions from cropland soils in Europe. Mitigation scenarios and sensitivity analyses are also presented to demonstrate how ECOSSE can be used to estimate the impact of future climate and land-use change on N2O emissions.
The Tibetan Plateau is a region that is highly sensitive to recent global warming, but the complexity and heterogeneity of its mountainous landscape can result in variable responses. In addition, the scarcity and brevity of regional instrumental and palaeoecological records still hamper our understanding of past and present patterns of environmental change. To investigate how the remote, high-alpine environments of the Nianbaoyeze Mountains, eastern Tibetan Plateau, are affected by climate change and human activity over the last similar to 600 years, we compared regional tree-ring studies with pollen and diatom remains archived in the dated sediments of Dongerwuka Lake (33.22A degrees N, 101.12A degrees E, 4,307 m a.s.l.). In agreement with previous studies from the eastern Tibetan Plateau, a strong coherence between our two juniper-based tree-ring chronologies from the Nianbaoyeze and the Anemaqin Mountains was observed, with pronounced cyclical variations in summer temperature reconstructions. A positive directional trend to warmer summer temperatures in the most recent decades, was, however, not observed in the tree-ring record. Likewise, our pollen and diatom spectra showed minimal change over the investigated time period. Although modest, the most notable change in the diatom relative abundances was a subtle decrease in the dominant planktonic Cyclotella ocellata and a concurrent increase in small, benthic fragilarioid taxa in the similar to 1820s, suggesting higher ecosystem variability. The pollen record subtly indicates three periods of increased cattle grazing activity (similar to 1400-1480 AD, similar to 1630-1760 AD, after 1850 AD), but shows generally no significant vegetation changes during past similar to 600 years. The minimal changes observed in the tree-ring, diatom and pollen records are consistent with the presence of localised cooling centres that are evident in instrumental and tree-ring data within the southeastern and eastern Tibetan Plateau. Given the minor changes in regional temperature records, our complacent palaeoecological profiles suggest that climatically induced ecological thresholds have not yet been crossed in the Nianbaoyeze Mountains region.