Projected Effects Of Climate Change Research Articles

Quantifying Soil Loss in the Brazilian Savanna Ecosystem: Current Rates and Anticipated Impact of Climate Changes

ABSTRACTThe Brazilian Savanna (Cerrado) is the second‐largest South American biome that corresponds to almost two‐third of the national agricultural production. Extensive agricultural‐driven land‐use changes have significantly altered the landscape, causing increased soil erosion. Furthermore, projections of climate change effects on the Cerrado raise concerns about the potential exacerbation of soil loss and its consequences on ecosystem sustainability. This study investigated soil loss for the Cerrado ecosystem by assessing current rates and projecting the potential effects of future climate change. Current soil loss was based on experimental plots (100 m2) during 7 years maintained under typical main land cover in Brazil (sugarcane, pasture, Cerrado, and bare soil). Erosivity, by using the Universal Soil Loss Equation (USLE), was estimated from observations, parameters of erodibility, and land cover. To assess the future soil loss (2100), we used the calibrated USLE equation with yearly erosivity derived from 12 downscaled and bias‐corrected SSP2‐4.5 and SSP5‐8.5 scenarios of CMIP6 climate model projections. Current agricultural practices induce considerable erosion, where sugarcane has 3.4 times higher soil loss as compared with the natural soil cover. Regarding future SSP2‐4.5 and SSP5‐8.5 scenarios (2100), we estimated an increase of 4.9% and 7.6% in soil loss, respectively, for all land covers. The observed soil loss rates underscore the critical importance of implementing sustainable land management practices to mitigate further soil degradation. Climate change may impose additional stress on the Cerrado ecosystem, amplifying the urgency for adaptive measures to safeguard this important biome.

Modelling and mapping carbon capture potential of farmed blue mussels in the Baltic Sea region

This study applies a regional Dynamic Energy Budget (DEB) model, enhanced to include biocalcification processes, to evaluate the carbon capture potential of farmed blue mussels (Mytilus edulis/trossulus) in the Baltic Sea. The research emphasises the long-term capture of carbon associated with shell formation, crucial for mitigating global warming effects. The model was built using a comprehensive pan-Baltic dataset that includes information on mussel growth, filtration and biodeposition rates, and nutrient content. The study also examined salinity, temperature, and chlorophyll a as key environmental factors influencing carbon capture in farmed mussels. Our findings revealed significant spatial and temporal variability in carbon dynamics under current and future environmental conditions. The tested future predictions are grounded in current scientific understanding and projections of climate change effects on the Baltic Sea. Notably, the outer Baltic Sea subbasins exhibited the highest carbon capture capacity with an average of 55 t (in the present scenario) and 65 t (under future environmental conditions) of carbon sequestrated per farm (0.25 ha) over a cultivation cycle – 17 months. Salinity was the main driver of predicted regional changes in carbon capture, while temperature and chlorophyll a had more pronounced local effects. This research advances our understanding of the role low trophic aquaculture plays in mitigating climate change. It highlights the importance of developing location-specific strategies for mussel farming that consider both local and regional environmental conditions. The results contribute to the wider discourse on sustainable aquaculture development and environmental conservation.

Do fishers follow fish displaced by climate warming?

Climate change is associated with altered oceanographic conditions that tend to shift the geographical distributions of fish. To assess the impact of climate change on fisheries, one must go beyond projections of catch potential and understand how fishers respond to moving target species. Many previous studies have explicitly or implicitly assumed that fishers follow fish that are displaced by climate warming. Here, we evaluate this assumption by analyzing a long-term, large-scale yet high-resolution dataset combined with a detailed oceanographic model. Our study case is the Atlantic cod (Gadhus morhua) fishery in Norway, one of the largest whitefish fisheries in the world, with little technological or judicial constraints on the potential spatial response of fishers. An oceanographic model is used to predict the areas that have been suitable for Atlantic cod spawning over the two last decades. We compare whether these areas overlap with actually observed fishing locations. While the areas that are suitable for spawning clearly predict how much fish are caught per trip, the suitability of an area does not predict how many vessels fish in a given area at a given point in time. In contrast, the number of vessels in the previous week and the previous year explain the current number of vessels in that area. Hence, future projections of climate change effects should account for the rich and nuanced behavioral responses of humans to project climate change effects on fisheries.

Three hundred years of past and future changes for native fish species in the upper Danube River Basin—Historical flow alterations versus future climate change

AbstractAimRivers belong to the most threatened ecosystems on Earth. Historical anthropogenic alterations have, and future climate change will further affect rivers and the species therein. While many studies have projected climate change effects on species, little is known about the severity of these changes compared to historical alterations. Here, we used a unique 300‐year time series of hydrological and climate data to explore the vulnerability of 48 native fish species in the upper Danube River Basin to past and potential future environmental changes.LocationUpper Danube River Basins (Germany and Austria).MethodsWe applied a climate niche factor analysis and calculated species‐specific vulnerability estimates based on modelled and observed hydrological and climate data from 1800 to 2100. We compared the estimated species vulnerabilities between two historical time intervals (1800–1830 and 1900–1930) and a future time interval (2070–2100, including the two representative concentration pathways 4.5 and 8.5) to an observed reference time interval (1970–2000). In addition, we identified the main environmental drivers of species vulnerability and their change over the past 200 years and for the predicted 100 years in the future.ResultsOur results showed that (i) in the past, species vulnerability was mainly driven by changes in discharge, while (ii) future potential vulnerabilities would be due to temperature. Moreover, we found that (iii) future environmental conditions for riverine fish species driven by temperature would change at a similar magnitude as past hydrological changes, driven by anthropogenic river alterations. Future changes, projected for the RCP 4.5, would result in moderate species vulnerability, whereas for the RCP 8.5, the vulnerability for all species would substantially increase compared to the historical conditions.Main ConclusionAccounting for an extended timeline uncovers the extent of historical pressures and provides unprecedented opportunities to proactively plan conservation strategies that are necessary to address future challenges.

Projected Climate Change Effects on Global Vegetation Growth: A Machine Learning Approach

In this study, a machine learning model was used to investigate the potential consequences of climate change on vegetation growth. The methodology involved analyzing the historical Normalized Difference Vegetation Index (NDVI) data and future climate projections under four Shared Socioeconomic Pathways (SSPs). Data from the Global Inventory Monitoring and Modeling System (GIMMS) dataset for the period 1981–2000 were used to train the machine learning model, while CMIP6 (Coupled Model Intercomparison Project Phase 6) global climate projections from 2021–2100 were employed to predict future NDVI values under different SSPs. The study results revealed that the global mean NDVI is projected to experience a significant increase from the period 1981–2000 to the period 2021–2040. Following this, the mean NDVI slightly increases under SSP126 and SSP245 while decreasing substantially under SSP370 and SSP585. In the near-term span of 2021–2040, the average NDVI value of SSP585 slightly exceeds that of SSP245 and SSP370, suggesting a positive vegetation development in response to a more pronounced temperature increase in the near term. However, if the trajectory of SSP585 persists, the mean NDVI will commence a decline over the subsequent three periods (2041–2060, 2061–2080, and 2080–2100) with a faster speed than that of SSP370. This decline is attributed to the adverse effects of a rapid temperature rise on vegetation. Based on the examination of individual continents, it is projected that the NDVI values in Africa, South America, and Oceania will decline over time, except under the scenario SSP126 during 2081–2100. On the other hand, the NDVI values in North America and Europe are anticipated to increase, with the exception of the scenario SSP585 during 2081–2100. Additionally, Asia is expected to follow an increasing trend, except under the scenario SSP126 during 2081–2100. In the larger scope, our research findings carry substantial implications for biodiversity preservation, greenhouse gas emission reduction, and efficient environmental management. The utilization of machine learning technology holds the potential to accurately predict future changes in vegetation growth and pinpoint areas where intervention is imperative.

Ongoing declines for the world’s amphibians in the face of emerging threats

Systematic assessments of species extinction risk at regular intervals are necessary for informing conservation action1,2. Ongoing developments in taxonomy, threatening processes and research further underscore the need for reassessment3,4. Here we report the findings of the second Global Amphibian Assessment, evaluating 8,011 species for the International Union for Conservation of Nature Red List of Threatened Species. We find that amphibians are the most threatened vertebrate class (40.7% of species are globally threatened). The updated Red List Index shows that the status of amphibians is deteriorating globally, particularly for salamanders and in the Neotropics. Disease and habitat loss drove 91% of status deteriorations between 1980 and 2004. Ongoing and projected climate change effects are now of increasing concern, driving 39% of status deteriorations since 2004, followed by habitat loss (37%). Although signs of species recoveries incentivize immediate conservation action, scaled-up investment is urgently needed to reverse the current trends.

Ocean acidification reduces thallus strength in a non-calcifying foundation seaweed

Climate change is causing unprecedented changes in terrestrial and aquatic ecosystems through the emission of greenhouse gases, including carbon dioxide (CO2). Approximately 30% of CO2 is taken up by the ocean ('ocean acidification', OA)1, which has profound effects on foundation seaweed species. Negative physical effects on calcifying algae are clear2, but studies on habitat-forming fleshy seaweeds have mainly focused on growth and less on thallus strength3,4. We exposed the habitat-forming brown seaweed Fucus vesiculosus to OA corresponding to projected climate change effects for the year 2100, and observed reduced apical thallus strength and greater loss of exposed individuals in the field. The tissue contained less calcium and magnesium, both of which are important for creating structural alginate matrices. Scanning electron microscopy (SEM) revealed tissue voids in the OA samples that were not present in seaweeds grown under ambient pCO2. We conclude that under OA, weakened F. vesiculosus will be at a significantly higher risk of physical damage and detachment.

Past and future climate change effects on the thermal regime and oxygen solubility of four peri-alpine lakes

Abstract. Long-term effects of climate change on lakes globally will include a substantial modification in the thermal regime and the oxygen solubility of lakes, resulting in the alteration of ecosystem processes, habitats, and concentrations of critical substances. Recent efforts have led to the development of long-term model projections of climate change effects on lake thermal regimes and oxygen solubility. However, such projections are hardly ever confronted with observations extending over multiple decades. Furthermore, global-scale forcing parameters in lake models present several limitations, such as the need of significant downscaling. In this study, the effects of climate change on thermal regime and oxygen solubility were analyzed in the four largest French peri-alpine lakes over 1850–2100. We tested several one-dimensional (1D) lake models' robustness for long-term variations based on up to 63 years of limnological data collected by the French Observatory of LAkes (OLA). Here, we evaluate the possibility of forcing mechanistic models by following the long-term evolution of shortwave radiation and air temperature while providing realistic seasonal trends for the other variables for which local-scale downscaling often lacks accuracy. Based on this approach, MyLake, forced by air temperatures and shortwave radiations, predicted accurately the variations in the lake thermal regime over the last 4 to 6 decades, with RMSE < 1.95 ∘C. Over the previous 3 decades, water temperatures have increased by 0.46 ∘C per decade (±0.02 ∘C) in the epilimnion and 0.33 ∘C per decade (±0.06 ∘C) in the hypolimnion. Concomitantly and due to thermal change, O2 solubility has decreased by −0.104 mg L−1 per decade (±0.005 mg L−1) and −0.096 mg L−1 per decade (±0.011 mg L−1) in the epilimnion and hypolimnion, respectively. Based on the shared socio-economic pathway SSP370 of the Intergovernmental Panel on Climate Change (IPCC), peri-alpine lakes could face an increase of 3.80 ∘C (±0.20 ∘C) in the next 70 years, accompanied by a decline of 1.0 mg L−1 (±0.1 mg L−1) of O2 solubility. Together, these results highlight a critical alteration in lake thermal and oxygen conditions in the coming decades, and a need for a better integration of long-term lake observatories data and lake models to anticipate climate effects on lake thermal regimes and habitats.

Infrastructure Adaptation and Climate Resilience for California’s National Forests

This paper describes the road infrastructure found in California’s national forests, their vulnerabilities, and specific measures that can be taken to adapt to projected climate change effects, thus minimizing damage from fires and storms. Over the past 40 years this region has been hit by numerous climate change–related events including droughts, major forest fires, major storms, and flooding. Billions of dollars in damage have been sustained and numerous lives lost. It is necessary now to assess vulnerabilities, rank resources at risk, and prioritize adaptation actions. The Forest Service has recently been involved in infrastructure vulnerability assessment and adaptation strategy projects involving climate model studies, interviews, a literature review, local workshops, website information, and publication of the project findings. Different agency vulnerability assessment methods have been reviewed to establish a functional assessment and risk analysis methodology. Efforts to mitigate the impacts of climate change have included greenhouse gas reduction from agency vehicles, evaluating alternative transportation routes, implementing energy-saving measures, and identifying “stormproofing” road design measures to reduce the vulnerability of roads to extreme climate-related events. Much of the effort has been the identification of road adaptation and resiliency measures, particularly measures that are practical and implementable at minimum cost. These measures include: routine road maintenance; relocating road segments as needed; adding trash racks and diversion prevention dips to prevent culvert failures; building stream simulation projects; protecting bridges from debris and scour; covering soil with deep-rooted vegetation; and using soil bioengineering stabilization and deep-patch shoulder reinforcement to prevent local slope failures.

Evaluation and application of SDSM to assess the projected climate change effects on the Tekeze watershed, Ethiopia

Evaluation and application of SDSM to assess the projected climate change effects on the Tekeze watershed, Ethiopia

Impacts of 2 and 4°C global warmings on extreme temperatures in Taiwan

AbstractExtreme temperatures were considered natural hazards because they could increase morbidity and mortality. Understanding the extreme temperature changes at different warming levels is crucial to climate change mitigation and adoption for human health. This study projected climate change effects on the intensity, occurrence, and duration of extreme temperatures in Taiwan with 2 and 4°C global warming scenarios using the Weather Research and Forecasting model. The future climate simulations were conducted with the pseudo‐global warming approach, and the future climate changes were obtained from the ensemble mean of simulations in the Coupled Model Intercomparison Project 5. The simulated daily mean temperature increased by 1.40 and 3.09°C under 2 and 4°C global warmings. In a warming world, the daily maximum temperature was projected to increase by 1.35–3.00°C, whereas the daily minimum temperature was even higher, leading to weaker diurnal temperature variation in most regions. The simulation results show that intensified heatwaves with frequent and prolonged durations become par for the course, whereas extremely cold days disappear gradually. The occurrence of heatwaves in the future is projected to be five times that in the current climate. Comparing the global warming impacts over different land‐use types, the heatwave occurrence over urban areas rose more quickly than over other land‐use types; forests are less vulnerable to global warming. On the contrary, the changes in extremely cold days over urban areas were weaker than over other land‐use types. Overall, the effects of global warming on temperature revealed that extreme events were more severe with increased temperature than with the mean state of air temperature. Nonlinear behaviours indicated that global warming should be limited to 2°C, and the additional 2°C warming (from 2 to 4°C) should be addressed carefully.

Trait‐based projections of climate change effects on global biome distributions

AbstractAimClimate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait‐based, statistical approach to model the influence of climate change on the global distribution of biomes.LocationGlobal.MethodsWe predicted the global distribution of plant community mean specific leaf area (SLA), height and wood density as a function of climate and soil characteristics using an ensemble of statistical models. Then, we predicted the probability of occurrence of biomes as a function of the three traits with a classification model. Finally, we projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios.ResultsWe estimated that under the low climate change scenario (sub)tropical biomes will expand (forest by 18%–22%, grassland by 9%–14% and xeric shrubland by 5%–8%), whereas tundra and temperate broadleaved and mixed forests contract by 30%–34% and 16%–21%, respectively. Our results also indicate that over 70%–75% of the current distribution of temperate broadleaved and mixed forests and temperate grasslands is projected to shift northwards. These changes become amplified under the extreme climate change scenario in which tundra is projected to lose more than half of its current extent.Main conclusionsOur results indicate considerable imminent alterations in the global distribution of biomes, with possibly major consequences for life on Earth. The level of accuracy of our model given the limited input data and the insights on how trait–environment relationships can influence biome distributions suggest that trait‐based correlative approaches are a promising tool to forecast vegetation change and to provide an independent, complementary line of evidence next to process‐based vegetation models.

Hydrological impacts of climate and land-use change on flow regime variations in upper Indus basin

Abstract Investigating the effects of climate and land-use changes on surface runoff is critical for water resources management. The majority of studies focused on projected climate change effects on surface runoff, while neglecting future land-use change. Therefore, the main aim of this article is to discriminate the impacts of projected climate and land-use changes on surface runoff using the Soil and Water Assessment Tool (SWAT) through the lens of the Upper Indus Basin, Pakistan. Future scenarios of the land-use and climate changes are predicted using cellular automata artificial neural network and four bias-corrected general circulation models, respectively. The historical record (2000–2013) was divided into the calibration period (2000–2008) and the validation period (2009–2013). The simulated results demonstrated that the SWAT model performed well. The results obtained from 2000 to 2013 show that climate change (61.61%) has a higher influence on river runoff than land-use change (38.39%). Both climate and land-use changes are predicted to increase future runoff depth in this basin. The influence of climate change (12.76–25.92%) is greater than land-use change (0.37–1.1%). Global weather data has good applicability for simulating hydrological responses in the region where conventional gauges are unavailable. The study discusses that both climate and land-use changes impact runoff depth and concludes with some suggestions for water resources managers to bring water environment sustainability.

Modeling the Pacific chub mackerel (Scomber japonicus) ecological niche and future scenarios in the northern Peruvian Current System

To understand and characterize the Pacific chub mackerel (Scomber japonicus) spatiotemporal distribution in the northern Peruvian Current System, this study characterized the ecological niche using the minimum volume ellipsoid (MVE) approach considering two meteorological conditions jointly: El Niño (EN) and La Niña (LN). For this purpose, the species presence records collected by the Peruvian onboard observer program from 1997 to 2018 were used. All presence records were matched with the date (day/month/year) and location (longitude, latitude) of the corresponding oceanographic variables (sea surface temperature [SST], sea surface salinity [SSS], chlorophyll, and oxygen). Also, the future projected climate change effects on chub mackerel spatiotemporal distribution under Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios by mid- (2040–2050) and end‐of‐the‐century (2090–2100) were investigated. Ellipsoid evaluations demonstrated that models calibrated with SST and SSS had good performance. Projections for EN conditions predicted areas with high environmental suitability close and along the Peruvian coast. Contrastingly, during LN these areas were extended to the oceanic zone. The projected future scenarios showed that for the RCP 4.5 scenario, environmental suitability maps were similar to those found in LN but with persistent distribution in south-central Peru. For the RCP 8.5 scenario, habitats tended to be coastal. Based on climate refugia –areas where the bulk of the species may aggregate under future environmental change with the potential to re-expand once the stress abates–, the RCP 4.5 scenario did not show changes in the hotspots; conversely, the RCP 8.5 scenario predicted a reduction of around 47% of hotspots from 2040–2050 to 2090–2100 at 10° S-18° S. Finally, the consideration of extreme conditions (EN and LN) in model calibration can potentially generate models with good performance allowing to better characterize species niche when the data is restricted by political boundaries. Nevertheless, further testing must be performed to assert this idea.

Strategy for achieving long-term energy efficiency of European single-family buildings through passive climate adaptation

The presented study aims to clarify the implications of passive design measures on heating and cooling energy use of single-family residential buildings under European representative climates. In order to address this matter, different values of thermal transmittance (opaque and transparent), window to floor ratio, window distribution, shape factor, diurnal heat storage capacity, external opaque surface solar absorptivity and natural ventilation cooling rates were combined in 496,800 building energy models, which were simulated at eight locations. Because buildings are in use for many decades, the energy use simulations were made considering the projected climate change up to the end of the 21st century. The results delivered a set of the most effective passive design measures for achieving low energy use in buildings regarding climate type and period. A lower window to floor ratio was identified as the most universally applicable design measure to counterbalance the projected effect of a warming climate. In contrast, other measures vary according to climate type and studied period. Furthermore, it was concluded that it is difficult to neutralise the projected climate change effects on buildings' energy use, even when applying the best performing combination of passive design measures. However, reasonably low energy use can still be assured solely by passive building design, especially in oceanic, warm, and some temperate climate locations. Therefore, the identified trends in energy use and passive design measures represent the foundation for strategies and guidelines aimed at future-proof energy-efficient buildings.

Comparative life cycle assessment of various energy efficiency designs of a container-based housing unit in China: A case study

Providing sustainable and affordable housing in rapidly developing regions in East Asia is an essential need, which can be satisfied by the market implementation of prefabricated, modular units, with a high energy-efficient performance. This study presents a comparative analysis of a factory-made residential unit, produced and located in Shanghai, China. A combination of energy analyses and life-cycle assessments is performed to quantify the life-cycle impacts related to various energy efficiency designs (convectional, low-energy, net-zero energy and off-grid) of a building module, developed from a new shipping container. The life-cycle assessment results indicate that the net-zero energy design strategy has the lowest life-cycle impacts in all categories, with 26% reduction in water consumption and up to 86% reduction in terms of global warming potential with respect to the convectional, baseline design. The ambition of becoming independent from the local electricity grid in the off-grid design results in nearly two-fold larger PV system when compared to the net-zero energy design, resulting in average 59% increase of total life cycle impacts. The sensitivity analysis shows that projected climate change effects have a minor influence on the life-cycle impacts, whereas the potential reuse of the building structure provides significant environmental benefits. Comparison with existing literature studies demonstrates the significant GHG emissions mitigation potential related to the implementation of off-grid and zero energy buildings in rural, remote, or post-disaster areas with limited electricity access and energy facilities based on fossil fuels.

To What Extent Can the Legal Strategies Employed to Curb the Global Pandemic (Coronavirus) Aid Climate Change and Global Warming Mitigation if Transposed?

This paper suggests that some of the common policies and decrees made by many countries to curb the spread of the Coronavirus (a global pandemic) may also be adoptable to mitigate climate change or reduce greenhouse gas emissions and invariably contribute to the world’s ozone layer repair, considering that both issues are global in nature. However, the article pinpoints some adjustments that may have to be made to some of these rules for them to be transposable for climate change mitigation. Distinctively the paper encourages that although some of these changes imposed by the law may seem extraneous, however, they are vital sacrifices that must be made if the projected climate change effects shall not overcome the human race. According to Antonio Guterres (UN general Secretary): the challenge is a global one and the world must remain resilient in resolving it.

How do forest landscapes respond to elevated CO2 and ozone? Scaling Aspen‐FACE plot‐scale experimental results

AbstractThe Aspen‐FACE (Free‐Air Carbon Enrichment) experiment was an 11‐yr study of the effect of elevated CO2 and ozone (alone and in combination) on the growth productivity of model aspen communities (pure aspen, aspen‐birch, and aspen‐maple) in the field in northern Wisconsin, USA. Uncertainty remains about how these short‐term plot‐level responses might play out at landscape scales where climate change, competition, succession, and disturbances interact with tree‐level responses. In this study, we used a recent physiology‐based approach (PnET‐Succession v3.1) within the forest landscape model LANDIS‐II to scale the site‐scale FACE results to landscape extents by mechanistically accounting for the globally changing drivers of CO2, ozone, temperature, and precipitation. We conducted a factorial simulation experiment to test five hypotheses about the effects of three treatments (CO2 concentration, cumulative ozone exposure, and disturbance). CO2 was clearly the dominant driver of landscape response, with disturbance also having a large effect. Ozone was not a dominant driver of landscape dynamics or total landscape biomass, but its negative effect on mean landscape biomass was nevertheless significant. We found that CO2 mitigation of water stress may not have a major effect on species composition or biomass accumulation. We found that species diversity was somewhat decreased by elevated CO2 as expected, but somewhat increased by O3, contrary to expectations. The spatial pattern of the landscape was minimally affected by the treatments. While rising CO2 concentrations have some mitigating effect on the negative O3 effect on the species studied, additional research is needed to confirm whether researchers and managers can be justified in disregarding O3 as a primary driver of forest dynamics in other ecosystems. Our results also add more support to the growing consensus that projections of climate change effects must include robust, direct links between CO2 and tree growth and competition; temperature effects (as demonstrated elsewhere) appear to be less by comparison.

Wetland restoration design modifications to mitigate climate change impacts at Delaware Water Gap National Recreation Area: A case study report

Author(s): Noon, Kevin F. | Abstract: Historic temperature and precipitation trends, and their projected climate change effects, were used to inform the development of wetland design tactics to restore a 30-acre degraded wetland at Delaware Water Gap National Recreation Area. The adverse effects of climate change to be addressed in the restoration design include increasing average daily air temperatures, rising stream and groundwater temperatures, increasing stream erosion, increasing precipitation, and increasing lake evaporation. Specific actions or tactics were developed that provide prescriptive direction in how restoration strategies can be translated to changes in on-the-ground conditions. Traditional on-the-ground tactics are described, along with modifications to the traditional tactics that should facilitate adaptation and increase the system’s capacity to survive adverse effects of climate change.

Climate projections for glacier change modelling over the Himalayas.

Glaciers are of key importance to freshwater supplies in the Himalayan region. Their growth or decline is among other factors determined by an interaction of 2‐m air temperature (TAS) and precipitation rate (PR) and thereof derived positive degree days (PDD) and snow and ice accumulation (SAC). To investigate determining factors in climate projections, we use a model ensemble consisting of 36 CMIP5 general circulation models (GCMs) and 13 regional climate models (RCMs) of two Asian CORDEX domains for two different representative concentration pathways (RCP4.5 and RCP8.5). First, we downsize the ensemble in respect to the models' ability to correctly reproduce dominant circulation patterns (i.e., the Indian summer monsoon [ISM] and western disturbances [WDs]) as well as elevation‐dependent trend signals in winter. Within this evaluation, a newly produced data set for the Indus, Ganges and Brahmaputra catchments is used as observational data. The reanalyses WFDEI, ERA‐Interim, NCEP/NCAR and JRA‐55 are used to further account for observational uncertainty. In a next step, remaining TAS and PR data are bias corrected applying a new bias adjustment method, scale distribution mapping, and subsequently PDD and SAC computed. Finally, we identify and quantify projected climate change effects. Until the end of the century, the ensemble indicates a rise of PDD, especially during summer and for lower altitudes. Also TAS is rising, though the highest increases are shown for higher altitudes and between December and April (DJFMA). PRs connected to the ISM are projected to robustly increase, while signals for PR changes during DJFMA show a higher level of uncertainty and spatial heterogeneity. However, a robust decline in solid precipitation is projected over our research domain, with the exception of a small area in the high mountain Indus catchment where no clear signal emerges.